{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "<p>假设,我们现在有一个新的温度计,遗憾的是,该温度计没有标明其度量单位,因此，我们需要使用旧的温度计来确定新温度计的度量值(旧温度计是摄氏度)</p>"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import torch\n",
    "import matplotlib.pyplot as plt\n",
    "t_c =[0.5,14.0,15.0,28.0,11.0,8.0,3.0,-4.0,6.0,13.0,21.0] # 旧温度计\n",
    "t_u =[35.7,55.9,58.2,81.9,56.3,48.9,33.9,21.8,48.4,60.4,68.4] # 新温度计\n",
    "\n",
    "t_c = torch.tensor(t_c)\n",
    "t_u = torch.tensor(t_u)\n",
    "\n",
    "# 可视化数据\n",
    "plt.scatter(t_u.numpy(),t_c.numpy())\n",
    "plt.xlabel('new')\n",
    "plt.ylabel('old')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-12T01:04:18.926591400Z",
     "start_time": "2023-10-12T01:03:45.136898900Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "outputs": [],
   "source": [
    "## 选择线性模型做尝试\n",
    "def model(t_u,w,b):\n",
    "    return t_u*w +b\n",
    "\n",
    "## 损失函数\n",
    "def loss_fn(t_p,t_c):\n",
    "    '''\n",
    "    :param t_p: 预测值\n",
    "    :param t_c: 实际值\n",
    "    :return: 损失值\n",
    "    '''\n",
    "    squared_diffs = (t_p-t_c)**2\n",
    "    return squared_diffs.mean() # 返回损失值的平均数"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-12T01:14:05.805412200Z",
     "start_time": "2023-10-12T01:14:05.773372400Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [
    {
     "data": {
      "text/plain": "tensor([35.7000, 55.9000, 58.2000, 81.9000, 56.3000, 48.9000, 33.9000, 21.8000,\n        48.4000, 60.4000, 68.4000])"
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 求出预测值\n",
    "w = torch.ones(())\n",
    "b = torch.zeros(())\n",
    "t_p = model(t_u,w,b)\n",
    "t_p"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-12T01:39:43.385897200Z",
     "start_time": "2023-10-12T01:39:42.953986100Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor(1763.8848)\n"
     ]
    }
   ],
   "source": [
    "# 计算损失值\n",
    "loss = loss_fn(t_p,t_c)\n",
    "print(loss)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-12T01:47:19.158291700Z",
     "start_time": "2023-10-12T01:47:18.558275200Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "outputs": [],
   "source": [
    "### 减小损失\n",
    "# 数值微分求导\n",
    "delta = 0.1\n",
    "loss_rate_of_change_w =  (loss_fn(model(t_u,w+delta,b),t_c)-loss_fn(model(t_u,w-delta,b),t_c))/(2.0*delta) # 获得导数"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-12T01:58:12.283173700Z",
     "start_time": "2023-10-12T01:58:12.253176600Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [],
   "source": [
    "# 更新权重w\n",
    "learning_rate =1e-2\n",
    "w = w-learning_rate*loss_rate_of_change_w"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-12T02:02:21.249010600Z",
     "start_time": "2023-10-12T02:02:21.230672Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "outputs": [],
   "source": [
    "# 更新b\n",
    "loss_rate_of_change_b = (\n",
    "    loss_fn(model(t_u,w+delta,b),t_c)-\n",
    "    loss_fn(model(t_u,w-delta,b),t_c)\n",
    ")/(2*delta)\n",
    "b = b-delta*loss_rate_of_change_b"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-12T02:11:25.208073900Z",
     "start_time": "2023-10-12T02:11:25.183069100Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "outputs": [],
   "source": [
    "def dloss_fn(t_p,t_c):\n",
    "    dsq_diffs = 2*(t_p-t_c)/t_p.size(0) # 这个触发来自均值的导数\n",
    "    return dsq_diffs\n",
    "\n",
    "def dmodel_dw(t_u,w,b):\n",
    "    return t_u\n",
    "\n",
    "def dmodel_db(t_u,w,b):\n",
    "    return 1.0"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-12T02:25:51.111266Z",
     "start_time": "2023-10-12T02:25:51.095267Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "outputs": [],
   "source": [
    "## 定义梯度函数\n",
    "def grad_fn(t_u,t_c,t_p,w,b):\n",
    "    dloss_dtp = dloss_fn(t_p,t_c)\n",
    "    dloss_dw = dloss_dtp * dmodel_dw(t_u,w,b) # 求w的导数\n",
    "    dloss_db =dloss_dtp*dmodel_db(t_u,w,b) # 求b的导数\n",
    "    return torch.stack([dloss_dw.sum(),dloss_db.sum()])"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-12T02:29:33.736605400Z",
     "start_time": "2023-10-12T02:29:33.653570500Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 1,Loss: 1763.884766\n",
      "\tgrad: tensor([4517.2964,   82.6000])\n",
      "\tparams: tensor([-44.1730,  -0.8260])\n",
      "Epoch: 2,Loss: 5802484.500000\n",
      "\tgrad: tensor([-261257.4062,   -4598.9702])\n",
      "\tparams: tensor([2568.4011,   45.1637])\n",
      "Epoch: 3,Loss: 19408029696.000000\n",
      "\tgrad: tensor([15109614.0000,   266155.6875])\n",
      "\tparams: tensor([-148527.7344,   -2616.3931])\n",
      "Epoch: 4,Loss: 64915905708032.000000\n",
      "\tgrad: tensor([-8.7385e+08, -1.5393e+07])\n",
      "\tparams: tensor([8589999.0000,  151310.8906])\n",
      "Epoch: 5,Loss: 217130525461053440.000000\n",
      "\tgrad: tensor([5.0539e+10, 8.9023e+08])\n",
      "\tparams: tensor([-4.9680e+08, -8.7510e+06])\n",
      "Epoch: 6,Loss: 726257583152928129024.000000\n",
      "\tgrad: tensor([-2.9229e+12, -5.1486e+10])\n",
      "\tparams: tensor([2.8732e+10, 5.0610e+08])\n",
      "Epoch: 7,Loss: 2429183416467662896627712.000000\n",
      "\tgrad: tensor([1.6904e+14, 2.9776e+12])\n",
      "\tparams: tensor([-1.6617e+12, -2.9270e+10])\n",
      "Epoch: 8,Loss: 8125122549611731432050262016.000000\n",
      "\tgrad: tensor([-9.7764e+15, -1.7221e+14])\n",
      "\tparams: tensor([9.6102e+13, 1.6928e+12])\n",
      "Epoch: 9,Loss: 27176882120842590626938030653440.000000\n",
      "\tgrad: tensor([5.6541e+17, 9.9596e+15])\n",
      "\tparams: tensor([-5.5580e+15, -9.7903e+13])\n",
      "Epoch: 10,Loss: 90901105189019073810297959556841472.000000\n",
      "\tgrad: tensor([-3.2700e+19, -5.7600e+17])\n",
      "\tparams: tensor([3.2144e+17, 5.6621e+15])\n",
      "Epoch: 11,Loss: inf\n",
      "\tgrad: tensor([1.8912e+21, 3.3313e+19])\n",
      "\tparams: tensor([-1.8590e+19, -3.2746e+17])\n",
      "Epoch: 12,Loss: inf\n",
      "\tgrad: tensor([-1.0937e+23, -1.9266e+21])\n",
      "\tparams: tensor([1.0752e+21, 1.8939e+19])\n",
      "Epoch: 13,Loss: inf\n",
      "\tgrad: tensor([6.3256e+24, 1.1142e+23])\n",
      "\tparams: tensor([-6.2181e+22, -1.0953e+21])\n",
      "Epoch: 14,Loss: inf\n",
      "\tgrad: tensor([-3.6584e+26, -6.4441e+24])\n",
      "\tparams: tensor([3.5962e+24, 6.3346e+22])\n",
      "Epoch: 15,Loss: inf\n",
      "\tgrad: tensor([2.1158e+28, 3.7269e+26])\n",
      "\tparams: tensor([-2.0798e+26, -3.6636e+24])\n",
      "Epoch: 16,Loss: inf\n",
      "\tgrad: tensor([-1.2236e+30, -2.1554e+28])\n",
      "\tparams: tensor([1.2028e+28, 2.1188e+26])\n",
      "Epoch: 17,Loss: inf\n",
      "\tgrad: tensor([7.0769e+31, 1.2466e+30])\n",
      "\tparams: tensor([-6.9566e+29, -1.2254e+28])\n",
      "Epoch: 18,Loss: inf\n",
      "\tgrad: tensor([-4.0929e+33, -7.2095e+31])\n",
      "\tparams: tensor([4.0233e+31, 7.0869e+29])\n",
      "Epoch: 19,Loss: inf\n",
      "\tgrad: tensor([2.3671e+35, 4.1695e+33])\n",
      "\tparams: tensor([-2.3268e+33, -4.0987e+31])\n",
      "Epoch: 20,Loss: inf\n",
      "\tgrad: tensor([-1.3690e+37, -2.4114e+35])\n",
      "\tparams: tensor([1.3457e+35, 2.3704e+33])\n",
      "Epoch: 21,Loss: inf\n",
      "\tgrad: tensor([       inf, 1.3946e+37])\n",
      "\tparams: tensor([       -inf, -1.3709e+35])\n",
      "Epoch: 22,Loss: inf\n",
      "\tgrad: tensor([-inf, -inf])\n",
      "\tparams: tensor([nan, inf])\n",
      "Epoch: 23,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 24,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 25,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 26,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 27,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 28,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 29,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 30,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 31,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 32,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 33,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 34,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 35,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 36,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 37,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 38,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 39,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 40,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 41,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 42,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 43,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 44,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 45,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 46,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 47,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 48,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 49,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 50,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 51,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 52,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 53,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 54,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 55,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 56,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 57,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 58,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 59,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 60,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 61,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 62,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 63,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 64,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 65,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 66,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 67,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 68,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 69,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 70,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 71,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 72,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 73,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 74,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 75,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 76,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 77,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 78,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 79,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 80,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 81,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 82,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 83,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 84,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 85,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 86,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 87,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 88,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 89,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 90,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 91,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 92,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 93,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 94,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 95,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 96,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 97,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 98,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 99,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n",
      "Epoch: 100,Loss: nan\n",
      "\tgrad: tensor([nan, nan])\n",
      "\tparams: tensor([nan, nan])\n"
     ]
    },
    {
     "data": {
      "text/plain": "tensor([nan, nan])"
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def training_loop(n_epochs,learning_rate,params,t_u,t_c):\n",
    "    for epoch in range(1,n_epochs+1):\n",
    "        w,b = params\n",
    "        t_p = model(t_u,w,b) # 正向传播\n",
    "        loss = loss_fn(t_p,t_c)\n",
    "        grad = grad_fn(t_u,t_c,t_p,w,b)\n",
    "        params = params-learning_rate*grad\n",
    "        print('Epoch: %d,Loss: %f'%(epoch,float(loss)))\n",
    "        print('\\tgrad:',grad)\n",
    "        print('\\tparams:',params)\n",
    "    return params\n",
    "\n",
    "training_loop(\n",
    "    n_epochs=100,\n",
    "    learning_rate=1e-2,\n",
    "    params=torch.tensor([1.0,0.0]),\n",
    "    t_u=t_u,\n",
    "    t_c=t_c\n",
    ")"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-12T02:46:16.010807900Z",
     "start_time": "2023-10-12T02:46:15.906806800Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 1,Loss: 1763.884766\n",
      "\tgrad: tensor([4517.2964,   82.6000])\n",
      "\tparams: tensor([ 0.5483, -0.0083])\n",
      "Epoch: 2,Loss: 323.090515\n",
      "\tgrad: tensor([1859.5493,   35.7843])\n",
      "\tparams: tensor([ 0.3623, -0.0118])\n",
      "Epoch: 3,Loss: 78.929634\n",
      "\tgrad: tensor([765.4666,  16.5122])\n",
      "\tparams: tensor([ 0.2858, -0.0135])\n",
      "Epoch: 4,Loss: 37.552845\n",
      "\tgrad: tensor([315.0790,   8.5787])\n",
      "\tparams: tensor([ 0.2543, -0.0143])\n",
      "Epoch: 5,Loss: 30.540283\n",
      "\tgrad: tensor([129.6733,   5.3127])\n",
      "\tparams: tensor([ 0.2413, -0.0149])\n",
      "Epoch: 6,Loss: 29.351154\n",
      "\tgrad: tensor([53.3495,  3.9682])\n",
      "\tparams: tensor([ 0.2360, -0.0153])\n",
      "Epoch: 7,Loss: 29.148884\n",
      "\tgrad: tensor([21.9304,  3.4148])\n",
      "\tparams: tensor([ 0.2338, -0.0156])\n",
      "Epoch: 8,Loss: 29.113848\n",
      "\tgrad: tensor([8.9964, 3.1869])\n",
      "\tparams: tensor([ 0.2329, -0.0159])\n",
      "Epoch: 9,Loss: 29.107145\n",
      "\tgrad: tensor([3.6721, 3.0930])\n",
      "\tparams: tensor([ 0.2325, -0.0162])\n",
      "Epoch: 10,Loss: 29.105247\n",
      "\tgrad: tensor([1.4803, 3.0544])\n",
      "\tparams: tensor([ 0.2324, -0.0166])\n",
      "Epoch: 11,Loss: 29.104168\n",
      "\tgrad: tensor([0.5781, 3.0384])\n",
      "\tparams: tensor([ 0.2323, -0.0169])\n",
      "Epoch: 12,Loss: 29.103222\n",
      "\tgrad: tensor([0.2066, 3.0318])\n",
      "\tparams: tensor([ 0.2323, -0.0172])\n",
      "Epoch: 13,Loss: 29.102295\n",
      "\tgrad: tensor([0.0537, 3.0291])\n",
      "\tparams: tensor([ 0.2323, -0.0175])\n",
      "Epoch: 14,Loss: 29.101379\n",
      "\tgrad: tensor([-0.0093,  3.0279])\n",
      "\tparams: tensor([ 0.2323, -0.0178])\n",
      "Epoch: 15,Loss: 29.100466\n",
      "\tgrad: tensor([-0.0353,  3.0274])\n",
      "\tparams: tensor([ 0.2323, -0.0181])\n",
      "Epoch: 16,Loss: 29.099548\n",
      "\tgrad: tensor([-0.0459,  3.0272])\n",
      "\tparams: tensor([ 0.2323, -0.0184])\n",
      "Epoch: 17,Loss: 29.098631\n",
      "\tgrad: tensor([-0.0502,  3.0270])\n",
      "\tparams: tensor([ 0.2323, -0.0187])\n",
      "Epoch: 18,Loss: 29.097717\n",
      "\tgrad: tensor([-0.0520,  3.0270])\n",
      "\tparams: tensor([ 0.2323, -0.0190])\n",
      "Epoch: 19,Loss: 29.096796\n",
      "\tgrad: tensor([-0.0528,  3.0269])\n",
      "\tparams: tensor([ 0.2323, -0.0193])\n",
      "Epoch: 20,Loss: 29.095881\n",
      "\tgrad: tensor([-0.0531,  3.0268])\n",
      "\tparams: tensor([ 0.2323, -0.0196])\n",
      "Epoch: 21,Loss: 29.094959\n",
      "\tgrad: tensor([-0.0533,  3.0268])\n",
      "\tparams: tensor([ 0.2323, -0.0199])\n",
      "Epoch: 22,Loss: 29.094049\n",
      "\tgrad: tensor([-0.0533,  3.0267])\n",
      "\tparams: tensor([ 0.2323, -0.0202])\n",
      "Epoch: 23,Loss: 29.093134\n",
      "\tgrad: tensor([-0.0533,  3.0267])\n",
      "\tparams: tensor([ 0.2323, -0.0205])\n",
      "Epoch: 24,Loss: 29.092216\n",
      "\tgrad: tensor([-0.0533,  3.0266])\n",
      "\tparams: tensor([ 0.2323, -0.0208])\n",
      "Epoch: 25,Loss: 29.091301\n",
      "\tgrad: tensor([-0.0533,  3.0266])\n",
      "\tparams: tensor([ 0.2323, -0.0211])\n",
      "Epoch: 26,Loss: 29.090385\n",
      "\tgrad: tensor([-0.0533,  3.0265])\n",
      "\tparams: tensor([ 0.2323, -0.0214])\n",
      "Epoch: 27,Loss: 29.089464\n",
      "\tgrad: tensor([-0.0533,  3.0265])\n",
      "\tparams: tensor([ 0.2323, -0.0217])\n",
      "Epoch: 28,Loss: 29.088551\n",
      "\tgrad: tensor([-0.0532,  3.0264])\n",
      "\tparams: tensor([ 0.2323, -0.0220])\n",
      "Epoch: 29,Loss: 29.087635\n",
      "\tgrad: tensor([-0.0533,  3.0264])\n",
      "\tparams: tensor([ 0.2323, -0.0223])\n",
      "Epoch: 30,Loss: 29.086714\n",
      "\tgrad: tensor([-0.0533,  3.0263])\n",
      "\tparams: tensor([ 0.2323, -0.0226])\n",
      "Epoch: 31,Loss: 29.085804\n",
      "\tgrad: tensor([-0.0532,  3.0262])\n",
      "\tparams: tensor([ 0.2324, -0.0229])\n",
      "Epoch: 32,Loss: 29.084888\n",
      "\tgrad: tensor([-0.0533,  3.0262])\n",
      "\tparams: tensor([ 0.2324, -0.0232])\n",
      "Epoch: 33,Loss: 29.083967\n",
      "\tgrad: tensor([-0.0533,  3.0261])\n",
      "\tparams: tensor([ 0.2324, -0.0235])\n",
      "Epoch: 34,Loss: 29.083057\n",
      "\tgrad: tensor([-0.0533,  3.0261])\n",
      "\tparams: tensor([ 0.2324, -0.0238])\n",
      "Epoch: 35,Loss: 29.082142\n",
      "\tgrad: tensor([-0.0532,  3.0260])\n",
      "\tparams: tensor([ 0.2324, -0.0241])\n",
      "Epoch: 36,Loss: 29.081221\n",
      "\tgrad: tensor([-0.0533,  3.0260])\n",
      "\tparams: tensor([ 0.2324, -0.0244])\n",
      "Epoch: 37,Loss: 29.080309\n",
      "\tgrad: tensor([-0.0533,  3.0259])\n",
      "\tparams: tensor([ 0.2324, -0.0247])\n",
      "Epoch: 38,Loss: 29.079390\n",
      "\tgrad: tensor([-0.0532,  3.0259])\n",
      "\tparams: tensor([ 0.2324, -0.0250])\n",
      "Epoch: 39,Loss: 29.078474\n",
      "\tgrad: tensor([-0.0533,  3.0258])\n",
      "\tparams: tensor([ 0.2324, -0.0253])\n",
      "Epoch: 40,Loss: 29.077562\n",
      "\tgrad: tensor([-0.0533,  3.0258])\n",
      "\tparams: tensor([ 0.2324, -0.0256])\n",
      "Epoch: 41,Loss: 29.076649\n",
      "\tgrad: tensor([-0.0533,  3.0257])\n",
      "\tparams: tensor([ 0.2324, -0.0259])\n",
      "Epoch: 42,Loss: 29.075731\n",
      "\tgrad: tensor([-0.0532,  3.0257])\n",
      "\tparams: tensor([ 0.2324, -0.0262])\n",
      "Epoch: 43,Loss: 29.074812\n",
      "\tgrad: tensor([-0.0533,  3.0256])\n",
      "\tparams: tensor([ 0.2324, -0.0265])\n",
      "Epoch: 44,Loss: 29.073895\n",
      "\tgrad: tensor([-0.0533,  3.0256])\n",
      "\tparams: tensor([ 0.2324, -0.0268])\n",
      "Epoch: 45,Loss: 29.072981\n",
      "\tgrad: tensor([-0.0533,  3.0255])\n",
      "\tparams: tensor([ 0.2324, -0.0271])\n",
      "Epoch: 46,Loss: 29.072069\n",
      "\tgrad: tensor([-0.0533,  3.0254])\n",
      "\tparams: tensor([ 0.2324, -0.0274])\n",
      "Epoch: 47,Loss: 29.071148\n",
      "\tgrad: tensor([-0.0533,  3.0254])\n",
      "\tparams: tensor([ 0.2324, -0.0277])\n",
      "Epoch: 48,Loss: 29.070234\n",
      "\tgrad: tensor([-0.0533,  3.0253])\n",
      "\tparams: tensor([ 0.2324, -0.0281])\n",
      "Epoch: 49,Loss: 29.069323\n",
      "\tgrad: tensor([-0.0533,  3.0253])\n",
      "\tparams: tensor([ 0.2325, -0.0284])\n",
      "Epoch: 50,Loss: 29.068401\n",
      "\tgrad: tensor([-0.0532,  3.0252])\n",
      "\tparams: tensor([ 0.2325, -0.0287])\n",
      "Epoch: 51,Loss: 29.067486\n",
      "\tgrad: tensor([-0.0533,  3.0252])\n",
      "\tparams: tensor([ 0.2325, -0.0290])\n",
      "Epoch: 52,Loss: 29.066566\n",
      "\tgrad: tensor([-0.0533,  3.0251])\n",
      "\tparams: tensor([ 0.2325, -0.0293])\n",
      "Epoch: 53,Loss: 29.065657\n",
      "\tgrad: tensor([-0.0533,  3.0251])\n",
      "\tparams: tensor([ 0.2325, -0.0296])\n",
      "Epoch: 54,Loss: 29.064741\n",
      "\tgrad: tensor([-0.0533,  3.0250])\n",
      "\tparams: tensor([ 0.2325, -0.0299])\n",
      "Epoch: 55,Loss: 29.063826\n",
      "\tgrad: tensor([-0.0532,  3.0250])\n",
      "\tparams: tensor([ 0.2325, -0.0302])\n",
      "Epoch: 56,Loss: 29.062910\n",
      "\tgrad: tensor([-0.0533,  3.0249])\n",
      "\tparams: tensor([ 0.2325, -0.0305])\n",
      "Epoch: 57,Loss: 29.061995\n",
      "\tgrad: tensor([-0.0532,  3.0249])\n",
      "\tparams: tensor([ 0.2325, -0.0308])\n",
      "Epoch: 58,Loss: 29.061079\n",
      "\tgrad: tensor([-0.0533,  3.0248])\n",
      "\tparams: tensor([ 0.2325, -0.0311])\n",
      "Epoch: 59,Loss: 29.060169\n",
      "\tgrad: tensor([-0.0533,  3.0248])\n",
      "\tparams: tensor([ 0.2325, -0.0314])\n",
      "Epoch: 60,Loss: 29.059248\n",
      "\tgrad: tensor([-0.0533,  3.0247])\n",
      "\tparams: tensor([ 0.2325, -0.0317])\n",
      "Epoch: 61,Loss: 29.058336\n",
      "\tgrad: tensor([-0.0533,  3.0247])\n",
      "\tparams: tensor([ 0.2325, -0.0320])\n",
      "Epoch: 62,Loss: 29.057415\n",
      "\tgrad: tensor([-0.0534,  3.0246])\n",
      "\tparams: tensor([ 0.2325, -0.0323])\n",
      "Epoch: 63,Loss: 29.056507\n",
      "\tgrad: tensor([-0.0533,  3.0245])\n",
      "\tparams: tensor([ 0.2325, -0.0326])\n",
      "Epoch: 64,Loss: 29.055586\n",
      "\tgrad: tensor([-0.0532,  3.0245])\n",
      "\tparams: tensor([ 0.2325, -0.0329])\n",
      "Epoch: 65,Loss: 29.054674\n",
      "\tgrad: tensor([-0.0533,  3.0244])\n",
      "\tparams: tensor([ 0.2325, -0.0332])\n",
      "Epoch: 66,Loss: 29.053761\n",
      "\tgrad: tensor([-0.0533,  3.0244])\n",
      "\tparams: tensor([ 0.2325, -0.0335])\n",
      "Epoch: 67,Loss: 29.052843\n",
      "\tgrad: tensor([-0.0533,  3.0243])\n",
      "\tparams: tensor([ 0.2325, -0.0338])\n",
      "Epoch: 68,Loss: 29.051929\n",
      "\tgrad: tensor([-0.0532,  3.0243])\n",
      "\tparams: tensor([ 0.2326, -0.0341])\n",
      "Epoch: 69,Loss: 29.051012\n",
      "\tgrad: tensor([-0.0533,  3.0242])\n",
      "\tparams: tensor([ 0.2326, -0.0344])\n",
      "Epoch: 70,Loss: 29.050098\n",
      "\tgrad: tensor([-0.0532,  3.0242])\n",
      "\tparams: tensor([ 0.2326, -0.0347])\n",
      "Epoch: 71,Loss: 29.049183\n",
      "\tgrad: tensor([-0.0533,  3.0241])\n",
      "\tparams: tensor([ 0.2326, -0.0350])\n",
      "Epoch: 72,Loss: 29.048273\n",
      "\tgrad: tensor([-0.0533,  3.0241])\n",
      "\tparams: tensor([ 0.2326, -0.0353])\n",
      "Epoch: 73,Loss: 29.047350\n",
      "\tgrad: tensor([-0.0532,  3.0240])\n",
      "\tparams: tensor([ 0.2326, -0.0356])\n",
      "Epoch: 74,Loss: 29.046442\n",
      "\tgrad: tensor([-0.0533,  3.0240])\n",
      "\tparams: tensor([ 0.2326, -0.0359])\n",
      "Epoch: 75,Loss: 29.045530\n",
      "\tgrad: tensor([-0.0532,  3.0239])\n",
      "\tparams: tensor([ 0.2326, -0.0362])\n",
      "Epoch: 76,Loss: 29.044611\n",
      "\tgrad: tensor([-0.0533,  3.0239])\n",
      "\tparams: tensor([ 0.2326, -0.0365])\n",
      "Epoch: 77,Loss: 29.043699\n",
      "\tgrad: tensor([-0.0533,  3.0238])\n",
      "\tparams: tensor([ 0.2326, -0.0368])\n",
      "Epoch: 78,Loss: 29.042784\n",
      "\tgrad: tensor([-0.0533,  3.0238])\n",
      "\tparams: tensor([ 0.2326, -0.0371])\n",
      "Epoch: 79,Loss: 29.041870\n",
      "\tgrad: tensor([-0.0533,  3.0237])\n",
      "\tparams: tensor([ 0.2326, -0.0374])\n",
      "Epoch: 80,Loss: 29.040955\n",
      "\tgrad: tensor([-0.0532,  3.0236])\n",
      "\tparams: tensor([ 0.2326, -0.0377])\n",
      "Epoch: 81,Loss: 29.040039\n",
      "\tgrad: tensor([-0.0534,  3.0236])\n",
      "\tparams: tensor([ 0.2326, -0.0380])\n",
      "Epoch: 82,Loss: 29.039122\n",
      "\tgrad: tensor([-0.0533,  3.0235])\n",
      "\tparams: tensor([ 0.2326, -0.0383])\n",
      "Epoch: 83,Loss: 29.038210\n",
      "\tgrad: tensor([-0.0532,  3.0235])\n",
      "\tparams: tensor([ 0.2326, -0.0386])\n",
      "Epoch: 84,Loss: 29.037294\n",
      "\tgrad: tensor([-0.0533,  3.0234])\n",
      "\tparams: tensor([ 0.2326, -0.0389])\n",
      "Epoch: 85,Loss: 29.036379\n",
      "\tgrad: tensor([-0.0533,  3.0234])\n",
      "\tparams: tensor([ 0.2326, -0.0392])\n",
      "Epoch: 86,Loss: 29.035463\n",
      "\tgrad: tensor([-0.0532,  3.0233])\n",
      "\tparams: tensor([ 0.2326, -0.0395])\n",
      "Epoch: 87,Loss: 29.034554\n",
      "\tgrad: tensor([-0.0533,  3.0233])\n",
      "\tparams: tensor([ 0.2327, -0.0398])\n",
      "Epoch: 88,Loss: 29.033636\n",
      "\tgrad: tensor([-0.0532,  3.0232])\n",
      "\tparams: tensor([ 0.2327, -0.0401])\n",
      "Epoch: 89,Loss: 29.032722\n",
      "\tgrad: tensor([-0.0533,  3.0232])\n",
      "\tparams: tensor([ 0.2327, -0.0405])\n",
      "Epoch: 90,Loss: 29.031811\n",
      "\tgrad: tensor([-0.0533,  3.0231])\n",
      "\tparams: tensor([ 0.2327, -0.0408])\n",
      "Epoch: 91,Loss: 29.030895\n",
      "\tgrad: tensor([-0.0532,  3.0231])\n",
      "\tparams: tensor([ 0.2327, -0.0411])\n",
      "Epoch: 92,Loss: 29.029976\n",
      "\tgrad: tensor([-0.0532,  3.0230])\n",
      "\tparams: tensor([ 0.2327, -0.0414])\n",
      "Epoch: 93,Loss: 29.029066\n",
      "\tgrad: tensor([-0.0533,  3.0230])\n",
      "\tparams: tensor([ 0.2327, -0.0417])\n",
      "Epoch: 94,Loss: 29.028151\n",
      "\tgrad: tensor([-0.0532,  3.0229])\n",
      "\tparams: tensor([ 0.2327, -0.0420])\n",
      "Epoch: 95,Loss: 29.027235\n",
      "\tgrad: tensor([-0.0533,  3.0229])\n",
      "\tparams: tensor([ 0.2327, -0.0423])\n",
      "Epoch: 96,Loss: 29.026323\n",
      "\tgrad: tensor([-0.0533,  3.0228])\n",
      "\tparams: tensor([ 0.2327, -0.0426])\n",
      "Epoch: 97,Loss: 29.025410\n",
      "\tgrad: tensor([-0.0532,  3.0227])\n",
      "\tparams: tensor([ 0.2327, -0.0429])\n",
      "Epoch: 98,Loss: 29.024492\n",
      "\tgrad: tensor([-0.0532,  3.0227])\n",
      "\tparams: tensor([ 0.2327, -0.0432])\n",
      "Epoch: 99,Loss: 29.023582\n",
      "\tgrad: tensor([-0.0533,  3.0226])\n",
      "\tparams: tensor([ 0.2327, -0.0435])\n",
      "Epoch: 100,Loss: 29.022667\n",
      "\tgrad: tensor([-0.0532,  3.0226])\n",
      "\tparams: tensor([ 0.2327, -0.0438])\n"
     ]
    },
    {
     "data": {
      "text/plain": "tensor([ 0.2327, -0.0438])"
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "training_loop(\n",
    "    n_epochs=100,\n",
    "    learning_rate=1e-4,\n",
    "    params=torch.tensor([1.0,0.0]),\n",
    "    t_u=t_u,\n",
    "    t_c=t_c\n",
    ")"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-12T02:46:20.985122100Z",
     "start_time": "2023-10-12T02:46:20.861136600Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "outputs": [],
   "source": [
    "# 做归一化\n",
    "t_un = 0.1*t_u"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-12T02:47:30.157124400Z",
     "start_time": "2023-10-12T02:47:30.127118Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 1,Loss: 80.364342\n",
      "\tgrad: tensor([-77.6140, -10.6400])\n",
      "\tparams: tensor([1.7761, 0.1064])\n",
      "Epoch: 2,Loss: 37.574913\n",
      "\tgrad: tensor([-30.8623,  -2.3864])\n",
      "\tparams: tensor([2.0848, 0.1303])\n",
      "Epoch: 3,Loss: 30.871077\n",
      "\tgrad: tensor([-12.4631,   0.8587])\n",
      "\tparams: tensor([2.2094, 0.1217])\n",
      "Epoch: 4,Loss: 29.756193\n",
      "\tgrad: tensor([-5.2218,  2.1327])\n",
      "\tparams: tensor([2.2616, 0.1004])\n",
      "Epoch: 5,Loss: 29.507153\n",
      "\tgrad: tensor([-2.3715,  2.6310])\n",
      "\tparams: tensor([2.2853, 0.0740])\n",
      "Epoch: 6,Loss: 29.392456\n",
      "\tgrad: tensor([-1.2492,  2.8241])\n",
      "\tparams: tensor([2.2978, 0.0458])\n",
      "Epoch: 7,Loss: 29.298828\n",
      "\tgrad: tensor([-0.8071,  2.8970])\n",
      "\tparams: tensor([2.3059, 0.0168])\n",
      "Epoch: 8,Loss: 29.208717\n",
      "\tgrad: tensor([-0.6325,  2.9227])\n",
      "\tparams: tensor([ 2.3122, -0.0124])\n",
      "Epoch: 9,Loss: 29.119415\n",
      "\tgrad: tensor([-0.5633,  2.9298])\n",
      "\tparams: tensor([ 2.3178, -0.0417])\n",
      "Epoch: 10,Loss: 29.030489\n",
      "\tgrad: tensor([-0.5355,  2.9295])\n",
      "\tparams: tensor([ 2.3232, -0.0710])\n",
      "Epoch: 11,Loss: 28.941877\n",
      "\tgrad: tensor([-0.5240,  2.9264])\n",
      "\tparams: tensor([ 2.3284, -0.1003])\n",
      "Epoch: 12,Loss: 28.853565\n",
      "\tgrad: tensor([-0.5190,  2.9222])\n",
      "\tparams: tensor([ 2.3336, -0.1295])\n",
      "Epoch: 13,Loss: 28.765553\n",
      "\tgrad: tensor([-0.5165,  2.9175])\n",
      "\tparams: tensor([ 2.3388, -0.1587])\n",
      "Epoch: 14,Loss: 28.677851\n",
      "\tgrad: tensor([-0.5150,  2.9126])\n",
      "\tparams: tensor([ 2.3439, -0.1878])\n",
      "Epoch: 15,Loss: 28.590431\n",
      "\tgrad: tensor([-0.5138,  2.9077])\n",
      "\tparams: tensor([ 2.3491, -0.2169])\n",
      "Epoch: 16,Loss: 28.503319\n",
      "\tgrad: tensor([-0.5129,  2.9028])\n",
      "\tparams: tensor([ 2.3542, -0.2459])\n",
      "Epoch: 17,Loss: 28.416498\n",
      "\tgrad: tensor([-0.5120,  2.8979])\n",
      "\tparams: tensor([ 2.3593, -0.2749])\n",
      "Epoch: 18,Loss: 28.329973\n",
      "\tgrad: tensor([-0.5111,  2.8930])\n",
      "\tparams: tensor([ 2.3644, -0.3038])\n",
      "Epoch: 19,Loss: 28.243742\n",
      "\tgrad: tensor([-0.5102,  2.8881])\n",
      "\tparams: tensor([ 2.3695, -0.3327])\n",
      "Epoch: 20,Loss: 28.157804\n",
      "\tgrad: tensor([-0.5093,  2.8832])\n",
      "\tparams: tensor([ 2.3746, -0.3615])\n",
      "Epoch: 21,Loss: 28.072151\n",
      "\tgrad: tensor([-0.5084,  2.8783])\n",
      "\tparams: tensor([ 2.3797, -0.3903])\n",
      "Epoch: 22,Loss: 27.986797\n",
      "\tgrad: tensor([-0.5076,  2.8734])\n",
      "\tparams: tensor([ 2.3848, -0.4190])\n",
      "Epoch: 23,Loss: 27.901728\n",
      "\tgrad: tensor([-0.5067,  2.8685])\n",
      "\tparams: tensor([ 2.3899, -0.4477])\n",
      "Epoch: 24,Loss: 27.816950\n",
      "\tgrad: tensor([-0.5059,  2.8636])\n",
      "\tparams: tensor([ 2.3949, -0.4763])\n",
      "Epoch: 25,Loss: 27.732464\n",
      "\tgrad: tensor([-0.5050,  2.8588])\n",
      "\tparams: tensor([ 2.4000, -0.5049])\n",
      "Epoch: 26,Loss: 27.648256\n",
      "\tgrad: tensor([-0.5042,  2.8539])\n",
      "\tparams: tensor([ 2.4050, -0.5335])\n",
      "Epoch: 27,Loss: 27.564344\n",
      "\tgrad: tensor([-0.5033,  2.8490])\n",
      "\tparams: tensor([ 2.4101, -0.5620])\n",
      "Epoch: 28,Loss: 27.480707\n",
      "\tgrad: tensor([-0.5024,  2.8442])\n",
      "\tparams: tensor([ 2.4151, -0.5904])\n",
      "Epoch: 29,Loss: 27.397362\n",
      "\tgrad: tensor([-0.5016,  2.8394])\n",
      "\tparams: tensor([ 2.4201, -0.6188])\n",
      "Epoch: 30,Loss: 27.314295\n",
      "\tgrad: tensor([-0.5007,  2.8346])\n",
      "\tparams: tensor([ 2.4251, -0.6471])\n",
      "Epoch: 31,Loss: 27.231512\n",
      "\tgrad: tensor([-0.4999,  2.8297])\n",
      "\tparams: tensor([ 2.4301, -0.6754])\n",
      "Epoch: 32,Loss: 27.149010\n",
      "\tgrad: tensor([-0.4990,  2.8249])\n",
      "\tparams: tensor([ 2.4351, -0.7037])\n",
      "Epoch: 33,Loss: 27.066790\n",
      "\tgrad: tensor([-0.4982,  2.8201])\n",
      "\tparams: tensor([ 2.4401, -0.7319])\n",
      "Epoch: 34,Loss: 26.984844\n",
      "\tgrad: tensor([-0.4973,  2.8153])\n",
      "\tparams: tensor([ 2.4450, -0.7600])\n",
      "Epoch: 35,Loss: 26.903175\n",
      "\tgrad: tensor([-0.4965,  2.8106])\n",
      "\tparams: tensor([ 2.4500, -0.7881])\n",
      "Epoch: 36,Loss: 26.821791\n",
      "\tgrad: tensor([-0.4957,  2.8058])\n",
      "\tparams: tensor([ 2.4550, -0.8162])\n",
      "Epoch: 37,Loss: 26.740679\n",
      "\tgrad: tensor([-0.4948,  2.8010])\n",
      "\tparams: tensor([ 2.4599, -0.8442])\n",
      "Epoch: 38,Loss: 26.659838\n",
      "\tgrad: tensor([-0.4940,  2.7963])\n",
      "\tparams: tensor([ 2.4649, -0.8722])\n",
      "Epoch: 39,Loss: 26.579279\n",
      "\tgrad: tensor([-0.4931,  2.7915])\n",
      "\tparams: tensor([ 2.4698, -0.9001])\n",
      "Epoch: 40,Loss: 26.498987\n",
      "\tgrad: tensor([-0.4923,  2.7868])\n",
      "\tparams: tensor([ 2.4747, -0.9280])\n",
      "Epoch: 41,Loss: 26.418974\n",
      "\tgrad: tensor([-0.4915,  2.7820])\n",
      "\tparams: tensor([ 2.4796, -0.9558])\n",
      "Epoch: 42,Loss: 26.339228\n",
      "\tgrad: tensor([-0.4906,  2.7773])\n",
      "\tparams: tensor([ 2.4845, -0.9836])\n",
      "Epoch: 43,Loss: 26.259754\n",
      "\tgrad: tensor([-0.4898,  2.7726])\n",
      "\tparams: tensor([ 2.4894, -1.0113])\n",
      "Epoch: 44,Loss: 26.180548\n",
      "\tgrad: tensor([-0.4890,  2.7679])\n",
      "\tparams: tensor([ 2.4943, -1.0390])\n",
      "Epoch: 45,Loss: 26.101616\n",
      "\tgrad: tensor([-0.4881,  2.7632])\n",
      "\tparams: tensor([ 2.4992, -1.0666])\n",
      "Epoch: 46,Loss: 26.022947\n",
      "\tgrad: tensor([-0.4873,  2.7585])\n",
      "\tparams: tensor([ 2.5041, -1.0942])\n",
      "Epoch: 47,Loss: 25.944544\n",
      "\tgrad: tensor([-0.4865,  2.7538])\n",
      "\tparams: tensor([ 2.5089, -1.1217])\n",
      "Epoch: 48,Loss: 25.866417\n",
      "\tgrad: tensor([-0.4856,  2.7491])\n",
      "\tparams: tensor([ 2.5138, -1.1492])\n",
      "Epoch: 49,Loss: 25.788549\n",
      "\tgrad: tensor([-0.4848,  2.7444])\n",
      "\tparams: tensor([ 2.5186, -1.1766])\n",
      "Epoch: 50,Loss: 25.710938\n",
      "\tgrad: tensor([-0.4840,  2.7398])\n",
      "\tparams: tensor([ 2.5235, -1.2040])\n",
      "Epoch: 51,Loss: 25.633600\n",
      "\tgrad: tensor([-0.4832,  2.7351])\n",
      "\tparams: tensor([ 2.5283, -1.2314])\n",
      "Epoch: 52,Loss: 25.556524\n",
      "\tgrad: tensor([-0.4823,  2.7305])\n",
      "\tparams: tensor([ 2.5331, -1.2587])\n",
      "Epoch: 53,Loss: 25.479700\n",
      "\tgrad: tensor([-0.4815,  2.7258])\n",
      "\tparams: tensor([ 2.5379, -1.2860])\n",
      "Epoch: 54,Loss: 25.403149\n",
      "\tgrad: tensor([-0.4807,  2.7212])\n",
      "\tparams: tensor([ 2.5428, -1.3132])\n",
      "Epoch: 55,Loss: 25.326851\n",
      "\tgrad: tensor([-0.4799,  2.7166])\n",
      "\tparams: tensor([ 2.5476, -1.3403])\n",
      "Epoch: 56,Loss: 25.250811\n",
      "\tgrad: tensor([-0.4791,  2.7120])\n",
      "\tparams: tensor([ 2.5523, -1.3675])\n",
      "Epoch: 57,Loss: 25.175035\n",
      "\tgrad: tensor([-0.4783,  2.7074])\n",
      "\tparams: tensor([ 2.5571, -1.3945])\n",
      "Epoch: 58,Loss: 25.099512\n",
      "\tgrad: tensor([-0.4775,  2.7028])\n",
      "\tparams: tensor([ 2.5619, -1.4216])\n",
      "Epoch: 59,Loss: 25.024248\n",
      "\tgrad: tensor([-0.4766,  2.6982])\n",
      "\tparams: tensor([ 2.5667, -1.4485])\n",
      "Epoch: 60,Loss: 24.949236\n",
      "\tgrad: tensor([-0.4758,  2.6936])\n",
      "\tparams: tensor([ 2.5714, -1.4755])\n",
      "Epoch: 61,Loss: 24.874483\n",
      "\tgrad: tensor([-0.4750,  2.6890])\n",
      "\tparams: tensor([ 2.5762, -1.5024])\n",
      "Epoch: 62,Loss: 24.799976\n",
      "\tgrad: tensor([-0.4742,  2.6845])\n",
      "\tparams: tensor([ 2.5809, -1.5292])\n",
      "Epoch: 63,Loss: 24.725737\n",
      "\tgrad: tensor([-0.4734,  2.6799])\n",
      "\tparams: tensor([ 2.5857, -1.5560])\n",
      "Epoch: 64,Loss: 24.651739\n",
      "\tgrad: tensor([-0.4726,  2.6753])\n",
      "\tparams: tensor([ 2.5904, -1.5828])\n",
      "Epoch: 65,Loss: 24.577986\n",
      "\tgrad: tensor([-0.4718,  2.6708])\n",
      "\tparams: tensor([ 2.5951, -1.6095])\n",
      "Epoch: 66,Loss: 24.504494\n",
      "\tgrad: tensor([-0.4710,  2.6663])\n",
      "\tparams: tensor([ 2.5998, -1.6361])\n",
      "Epoch: 67,Loss: 24.431252\n",
      "\tgrad: tensor([-0.4702,  2.6617])\n",
      "\tparams: tensor([ 2.6045, -1.6628])\n",
      "Epoch: 68,Loss: 24.358257\n",
      "\tgrad: tensor([-0.4694,  2.6572])\n",
      "\tparams: tensor([ 2.6092, -1.6893])\n",
      "Epoch: 69,Loss: 24.285505\n",
      "\tgrad: tensor([-0.4686,  2.6527])\n",
      "\tparams: tensor([ 2.6139, -1.7159])\n",
      "Epoch: 70,Loss: 24.212999\n",
      "\tgrad: tensor([-0.4678,  2.6482])\n",
      "\tparams: tensor([ 2.6186, -1.7423])\n",
      "Epoch: 71,Loss: 24.140741\n",
      "\tgrad: tensor([-0.4670,  2.6437])\n",
      "\tparams: tensor([ 2.6232, -1.7688])\n",
      "Epoch: 72,Loss: 24.068733\n",
      "\tgrad: tensor([-0.4662,  2.6392])\n",
      "\tparams: tensor([ 2.6279, -1.7952])\n",
      "Epoch: 73,Loss: 23.996971\n",
      "\tgrad: tensor([-0.4654,  2.6347])\n",
      "\tparams: tensor([ 2.6326, -1.8215])\n",
      "Epoch: 74,Loss: 23.925446\n",
      "\tgrad: tensor([-0.4646,  2.6302])\n",
      "\tparams: tensor([ 2.6372, -1.8478])\n",
      "Epoch: 75,Loss: 23.854168\n",
      "\tgrad: tensor([-0.4638,  2.6258])\n",
      "\tparams: tensor([ 2.6418, -1.8741])\n",
      "Epoch: 76,Loss: 23.783125\n",
      "\tgrad: tensor([-0.4631,  2.6213])\n",
      "\tparams: tensor([ 2.6465, -1.9003])\n",
      "Epoch: 77,Loss: 23.712328\n",
      "\tgrad: tensor([-0.4623,  2.6169])\n",
      "\tparams: tensor([ 2.6511, -1.9265])\n",
      "Epoch: 78,Loss: 23.641773\n",
      "\tgrad: tensor([-0.4615,  2.6124])\n",
      "\tparams: tensor([ 2.6557, -1.9526])\n",
      "Epoch: 79,Loss: 23.571455\n",
      "\tgrad: tensor([-0.4607,  2.6080])\n",
      "\tparams: tensor([ 2.6603, -1.9787])\n",
      "Epoch: 80,Loss: 23.501379\n",
      "\tgrad: tensor([-0.4599,  2.6035])\n",
      "\tparams: tensor([ 2.6649, -2.0047])\n",
      "Epoch: 81,Loss: 23.431538\n",
      "\tgrad: tensor([-0.4591,  2.5991])\n",
      "\tparams: tensor([ 2.6695, -2.0307])\n",
      "Epoch: 82,Loss: 23.361937\n",
      "\tgrad: tensor([-0.4584,  2.5947])\n",
      "\tparams: tensor([ 2.6741, -2.0566])\n",
      "Epoch: 83,Loss: 23.292570\n",
      "\tgrad: tensor([-0.4576,  2.5903])\n",
      "\tparams: tensor([ 2.6787, -2.0825])\n",
      "Epoch: 84,Loss: 23.223436\n",
      "\tgrad: tensor([-0.4568,  2.5859])\n",
      "\tparams: tensor([ 2.6832, -2.1084])\n",
      "Epoch: 85,Loss: 23.154541\n",
      "\tgrad: tensor([-0.4560,  2.5815])\n",
      "\tparams: tensor([ 2.6878, -2.1342])\n",
      "Epoch: 86,Loss: 23.085882\n",
      "\tgrad: tensor([-0.4553,  2.5771])\n",
      "\tparams: tensor([ 2.6923, -2.1600])\n",
      "Epoch: 87,Loss: 23.017447\n",
      "\tgrad: tensor([-0.4545,  2.5727])\n",
      "\tparams: tensor([ 2.6969, -2.1857])\n",
      "Epoch: 88,Loss: 22.949251\n",
      "\tgrad: tensor([-0.4537,  2.5684])\n",
      "\tparams: tensor([ 2.7014, -2.2114])\n",
      "Epoch: 89,Loss: 22.881283\n",
      "\tgrad: tensor([-0.4529,  2.5640])\n",
      "\tparams: tensor([ 2.7060, -2.2370])\n",
      "Epoch: 90,Loss: 22.813549\n",
      "\tgrad: tensor([-0.4522,  2.5597])\n",
      "\tparams: tensor([ 2.7105, -2.2626])\n",
      "Epoch: 91,Loss: 22.746044\n",
      "\tgrad: tensor([-0.4514,  2.5553])\n",
      "\tparams: tensor([ 2.7150, -2.2882])\n",
      "Epoch: 92,Loss: 22.678766\n",
      "\tgrad: tensor([-0.4506,  2.5510])\n",
      "\tparams: tensor([ 2.7195, -2.3137])\n",
      "Epoch: 93,Loss: 22.611717\n",
      "\tgrad: tensor([-0.4499,  2.5466])\n",
      "\tparams: tensor([ 2.7240, -2.3392])\n",
      "Epoch: 94,Loss: 22.544899\n",
      "\tgrad: tensor([-0.4491,  2.5423])\n",
      "\tparams: tensor([ 2.7285, -2.3646])\n",
      "Epoch: 95,Loss: 22.478306\n",
      "\tgrad: tensor([-0.4483,  2.5380])\n",
      "\tparams: tensor([ 2.7330, -2.3900])\n",
      "Epoch: 96,Loss: 22.411934\n",
      "\tgrad: tensor([-0.4476,  2.5337])\n",
      "\tparams: tensor([ 2.7374, -2.4153])\n",
      "Epoch: 97,Loss: 22.345793\n",
      "\tgrad: tensor([-0.4468,  2.5294])\n",
      "\tparams: tensor([ 2.7419, -2.4406])\n",
      "Epoch: 98,Loss: 22.279875\n",
      "\tgrad: tensor([-0.4461,  2.5251])\n",
      "\tparams: tensor([ 2.7464, -2.4658])\n",
      "Epoch: 99,Loss: 22.214186\n",
      "\tgrad: tensor([-0.4453,  2.5208])\n",
      "\tparams: tensor([ 2.7508, -2.4910])\n",
      "Epoch: 100,Loss: 22.148710\n",
      "\tgrad: tensor([-0.4446,  2.5165])\n",
      "\tparams: tensor([ 2.7553, -2.5162])\n"
     ]
    },
    {
     "data": {
      "text/plain": "tensor([ 2.7553, -2.5162])"
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "training_loop(n_epochs=100,\n",
    "              learning_rate=1e-2,\n",
    "              params=torch.tensor([1.0,0.0]),\n",
    "              t_u=t_un,\n",
    "              t_c = t_c\n",
    "              )"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-12T02:48:28.965995Z",
     "start_time": "2023-10-12T02:48:28.846066700Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 1,Loss: 80.364342\n",
      "\tgrad: tensor([-77.6140, -10.6400])\n",
      "\tparams: tensor([1.7761, 0.1064])\n",
      "Epoch: 2,Loss: 37.574913\n",
      "\tgrad: tensor([-30.8623,  -2.3864])\n",
      "\tparams: tensor([2.0848, 0.1303])\n",
      "Epoch: 3,Loss: 30.871077\n",
      "\tgrad: tensor([-12.4631,   0.8587])\n",
      "\tparams: tensor([2.2094, 0.1217])\n",
      "Epoch: 4,Loss: 29.756193\n",
      "\tgrad: tensor([-5.2218,  2.1327])\n",
      "\tparams: tensor([2.2616, 0.1004])\n",
      "Epoch: 5,Loss: 29.507153\n",
      "\tgrad: tensor([-2.3715,  2.6310])\n",
      "\tparams: tensor([2.2853, 0.0740])\n",
      "Epoch: 6,Loss: 29.392456\n",
      "\tgrad: tensor([-1.2492,  2.8241])\n",
      "\tparams: tensor([2.2978, 0.0458])\n",
      "Epoch: 7,Loss: 29.298828\n",
      "\tgrad: tensor([-0.8071,  2.8970])\n",
      "\tparams: tensor([2.3059, 0.0168])\n",
      "Epoch: 8,Loss: 29.208717\n",
      "\tgrad: tensor([-0.6325,  2.9227])\n",
      "\tparams: tensor([ 2.3122, -0.0124])\n",
      "Epoch: 9,Loss: 29.119415\n",
      "\tgrad: tensor([-0.5633,  2.9298])\n",
      "\tparams: tensor([ 2.3178, -0.0417])\n",
      "Epoch: 10,Loss: 29.030489\n",
      "\tgrad: tensor([-0.5355,  2.9295])\n",
      "\tparams: tensor([ 2.3232, -0.0710])\n",
      "Epoch: 11,Loss: 28.941877\n",
      "\tgrad: tensor([-0.5240,  2.9264])\n",
      "\tparams: tensor([ 2.3284, -0.1003])\n",
      "Epoch: 12,Loss: 28.853565\n",
      "\tgrad: tensor([-0.5190,  2.9222])\n",
      "\tparams: tensor([ 2.3336, -0.1295])\n",
      "Epoch: 13,Loss: 28.765553\n",
      "\tgrad: tensor([-0.5165,  2.9175])\n",
      "\tparams: tensor([ 2.3388, -0.1587])\n",
      "Epoch: 14,Loss: 28.677851\n",
      "\tgrad: tensor([-0.5150,  2.9126])\n",
      "\tparams: tensor([ 2.3439, -0.1878])\n",
      "Epoch: 15,Loss: 28.590431\n",
      "\tgrad: tensor([-0.5138,  2.9077])\n",
      "\tparams: tensor([ 2.3491, -0.2169])\n",
      "Epoch: 16,Loss: 28.503319\n",
      "\tgrad: tensor([-0.5129,  2.9028])\n",
      "\tparams: tensor([ 2.3542, -0.2459])\n",
      "Epoch: 17,Loss: 28.416498\n",
      "\tgrad: tensor([-0.5120,  2.8979])\n",
      "\tparams: tensor([ 2.3593, -0.2749])\n",
      "Epoch: 18,Loss: 28.329973\n",
      "\tgrad: tensor([-0.5111,  2.8930])\n",
      "\tparams: tensor([ 2.3644, -0.3038])\n",
      "Epoch: 19,Loss: 28.243742\n",
      "\tgrad: tensor([-0.5102,  2.8881])\n",
      "\tparams: tensor([ 2.3695, -0.3327])\n",
      "Epoch: 20,Loss: 28.157804\n",
      "\tgrad: tensor([-0.5093,  2.8832])\n",
      "\tparams: tensor([ 2.3746, -0.3615])\n",
      "Epoch: 21,Loss: 28.072151\n",
      "\tgrad: tensor([-0.5084,  2.8783])\n",
      "\tparams: tensor([ 2.3797, -0.3903])\n",
      "Epoch: 22,Loss: 27.986797\n",
      "\tgrad: tensor([-0.5076,  2.8734])\n",
      "\tparams: tensor([ 2.3848, -0.4190])\n",
      "Epoch: 23,Loss: 27.901728\n",
      "\tgrad: tensor([-0.5067,  2.8685])\n",
      "\tparams: tensor([ 2.3899, -0.4477])\n",
      "Epoch: 24,Loss: 27.816950\n",
      "\tgrad: tensor([-0.5059,  2.8636])\n",
      "\tparams: tensor([ 2.3949, -0.4763])\n",
      "Epoch: 25,Loss: 27.732464\n",
      "\tgrad: tensor([-0.5050,  2.8588])\n",
      "\tparams: tensor([ 2.4000, -0.5049])\n",
      "Epoch: 26,Loss: 27.648256\n",
      "\tgrad: tensor([-0.5042,  2.8539])\n",
      "\tparams: tensor([ 2.4050, -0.5335])\n",
      "Epoch: 27,Loss: 27.564344\n",
      "\tgrad: tensor([-0.5033,  2.8490])\n",
      "\tparams: tensor([ 2.4101, -0.5620])\n",
      "Epoch: 28,Loss: 27.480707\n",
      "\tgrad: tensor([-0.5024,  2.8442])\n",
      "\tparams: tensor([ 2.4151, -0.5904])\n",
      "Epoch: 29,Loss: 27.397362\n",
      "\tgrad: tensor([-0.5016,  2.8394])\n",
      "\tparams: tensor([ 2.4201, -0.6188])\n",
      "Epoch: 30,Loss: 27.314295\n",
      "\tgrad: tensor([-0.5007,  2.8346])\n",
      "\tparams: tensor([ 2.4251, -0.6471])\n",
      "Epoch: 31,Loss: 27.231512\n",
      "\tgrad: tensor([-0.4999,  2.8297])\n",
      "\tparams: tensor([ 2.4301, -0.6754])\n",
      "Epoch: 32,Loss: 27.149010\n",
      "\tgrad: tensor([-0.4990,  2.8249])\n",
      "\tparams: tensor([ 2.4351, -0.7037])\n",
      "Epoch: 33,Loss: 27.066790\n",
      "\tgrad: tensor([-0.4982,  2.8201])\n",
      "\tparams: tensor([ 2.4401, -0.7319])\n",
      "Epoch: 34,Loss: 26.984844\n",
      "\tgrad: tensor([-0.4973,  2.8153])\n",
      "\tparams: tensor([ 2.4450, -0.7600])\n",
      "Epoch: 35,Loss: 26.903175\n",
      "\tgrad: tensor([-0.4965,  2.8106])\n",
      "\tparams: tensor([ 2.4500, -0.7881])\n",
      "Epoch: 36,Loss: 26.821791\n",
      "\tgrad: tensor([-0.4957,  2.8058])\n",
      "\tparams: tensor([ 2.4550, -0.8162])\n",
      "Epoch: 37,Loss: 26.740679\n",
      "\tgrad: tensor([-0.4948,  2.8010])\n",
      "\tparams: tensor([ 2.4599, -0.8442])\n",
      "Epoch: 38,Loss: 26.659838\n",
      "\tgrad: tensor([-0.4940,  2.7963])\n",
      "\tparams: tensor([ 2.4649, -0.8722])\n",
      "Epoch: 39,Loss: 26.579279\n",
      "\tgrad: tensor([-0.4931,  2.7915])\n",
      "\tparams: tensor([ 2.4698, -0.9001])\n",
      "Epoch: 40,Loss: 26.498987\n",
      "\tgrad: tensor([-0.4923,  2.7868])\n",
      "\tparams: tensor([ 2.4747, -0.9280])\n",
      "Epoch: 41,Loss: 26.418974\n",
      "\tgrad: tensor([-0.4915,  2.7820])\n",
      "\tparams: tensor([ 2.4796, -0.9558])\n",
      "Epoch: 42,Loss: 26.339228\n",
      "\tgrad: tensor([-0.4906,  2.7773])\n",
      "\tparams: tensor([ 2.4845, -0.9836])\n",
      "Epoch: 43,Loss: 26.259754\n",
      "\tgrad: tensor([-0.4898,  2.7726])\n",
      "\tparams: tensor([ 2.4894, -1.0113])\n",
      "Epoch: 44,Loss: 26.180548\n",
      "\tgrad: tensor([-0.4890,  2.7679])\n",
      "\tparams: tensor([ 2.4943, -1.0390])\n",
      "Epoch: 45,Loss: 26.101616\n",
      "\tgrad: tensor([-0.4881,  2.7632])\n",
      "\tparams: tensor([ 2.4992, -1.0666])\n",
      "Epoch: 46,Loss: 26.022947\n",
      "\tgrad: tensor([-0.4873,  2.7585])\n",
      "\tparams: tensor([ 2.5041, -1.0942])\n",
      "Epoch: 47,Loss: 25.944544\n",
      "\tgrad: tensor([-0.4865,  2.7538])\n",
      "\tparams: tensor([ 2.5089, -1.1217])\n",
      "Epoch: 48,Loss: 25.866417\n",
      "\tgrad: tensor([-0.4856,  2.7491])\n",
      "\tparams: tensor([ 2.5138, -1.1492])\n",
      "Epoch: 49,Loss: 25.788549\n",
      "\tgrad: tensor([-0.4848,  2.7444])\n",
      "\tparams: tensor([ 2.5186, -1.1766])\n",
      "Epoch: 50,Loss: 25.710938\n",
      "\tgrad: tensor([-0.4840,  2.7398])\n",
      "\tparams: tensor([ 2.5235, -1.2040])\n",
      "Epoch: 51,Loss: 25.633600\n",
      "\tgrad: tensor([-0.4832,  2.7351])\n",
      "\tparams: tensor([ 2.5283, -1.2314])\n",
      "Epoch: 52,Loss: 25.556524\n",
      "\tgrad: tensor([-0.4823,  2.7305])\n",
      "\tparams: tensor([ 2.5331, -1.2587])\n",
      "Epoch: 53,Loss: 25.479700\n",
      "\tgrad: tensor([-0.4815,  2.7258])\n",
      "\tparams: tensor([ 2.5379, -1.2860])\n",
      "Epoch: 54,Loss: 25.403149\n",
      "\tgrad: tensor([-0.4807,  2.7212])\n",
      "\tparams: tensor([ 2.5428, -1.3132])\n",
      "Epoch: 55,Loss: 25.326851\n",
      "\tgrad: tensor([-0.4799,  2.7166])\n",
      "\tparams: tensor([ 2.5476, -1.3403])\n",
      "Epoch: 56,Loss: 25.250811\n",
      "\tgrad: tensor([-0.4791,  2.7120])\n",
      "\tparams: tensor([ 2.5523, -1.3675])\n",
      "Epoch: 57,Loss: 25.175035\n",
      "\tgrad: tensor([-0.4783,  2.7074])\n",
      "\tparams: tensor([ 2.5571, -1.3945])\n",
      "Epoch: 58,Loss: 25.099512\n",
      "\tgrad: tensor([-0.4775,  2.7028])\n",
      "\tparams: tensor([ 2.5619, -1.4216])\n",
      "Epoch: 59,Loss: 25.024248\n",
      "\tgrad: tensor([-0.4766,  2.6982])\n",
      "\tparams: tensor([ 2.5667, -1.4485])\n",
      "Epoch: 60,Loss: 24.949236\n",
      "\tgrad: tensor([-0.4758,  2.6936])\n",
      "\tparams: tensor([ 2.5714, -1.4755])\n",
      "Epoch: 61,Loss: 24.874483\n",
      "\tgrad: tensor([-0.4750,  2.6890])\n",
      "\tparams: tensor([ 2.5762, -1.5024])\n",
      "Epoch: 62,Loss: 24.799976\n",
      "\tgrad: tensor([-0.4742,  2.6845])\n",
      "\tparams: tensor([ 2.5809, -1.5292])\n",
      "Epoch: 63,Loss: 24.725737\n",
      "\tgrad: tensor([-0.4734,  2.6799])\n",
      "\tparams: tensor([ 2.5857, -1.5560])\n",
      "Epoch: 64,Loss: 24.651739\n",
      "\tgrad: tensor([-0.4726,  2.6753])\n",
      "\tparams: tensor([ 2.5904, -1.5828])\n",
      "Epoch: 65,Loss: 24.577986\n",
      "\tgrad: tensor([-0.4718,  2.6708])\n",
      "\tparams: tensor([ 2.5951, -1.6095])\n",
      "Epoch: 66,Loss: 24.504494\n",
      "\tgrad: tensor([-0.4710,  2.6663])\n",
      "\tparams: tensor([ 2.5998, -1.6361])\n",
      "Epoch: 67,Loss: 24.431252\n",
      "\tgrad: tensor([-0.4702,  2.6617])\n",
      "\tparams: tensor([ 2.6045, -1.6628])\n",
      "Epoch: 68,Loss: 24.358257\n",
      "\tgrad: tensor([-0.4694,  2.6572])\n",
      "\tparams: tensor([ 2.6092, -1.6893])\n",
      "Epoch: 69,Loss: 24.285505\n",
      "\tgrad: tensor([-0.4686,  2.6527])\n",
      "\tparams: tensor([ 2.6139, -1.7159])\n",
      "Epoch: 70,Loss: 24.212999\n",
      "\tgrad: tensor([-0.4678,  2.6482])\n",
      "\tparams: tensor([ 2.6186, -1.7423])\n",
      "Epoch: 71,Loss: 24.140741\n",
      "\tgrad: tensor([-0.4670,  2.6437])\n",
      "\tparams: tensor([ 2.6232, -1.7688])\n",
      "Epoch: 72,Loss: 24.068733\n",
      "\tgrad: tensor([-0.4662,  2.6392])\n",
      "\tparams: tensor([ 2.6279, -1.7952])\n",
      "Epoch: 73,Loss: 23.996971\n",
      "\tgrad: tensor([-0.4654,  2.6347])\n",
      "\tparams: tensor([ 2.6326, -1.8215])\n",
      "Epoch: 74,Loss: 23.925446\n",
      "\tgrad: tensor([-0.4646,  2.6302])\n",
      "\tparams: tensor([ 2.6372, -1.8478])\n",
      "Epoch: 75,Loss: 23.854168\n",
      "\tgrad: tensor([-0.4638,  2.6258])\n",
      "\tparams: tensor([ 2.6418, -1.8741])\n",
      "Epoch: 76,Loss: 23.783125\n",
      "\tgrad: tensor([-0.4631,  2.6213])\n",
      "\tparams: tensor([ 2.6465, -1.9003])\n",
      "Epoch: 77,Loss: 23.712328\n",
      "\tgrad: tensor([-0.4623,  2.6169])\n",
      "\tparams: tensor([ 2.6511, -1.9265])\n",
      "Epoch: 78,Loss: 23.641773\n",
      "\tgrad: tensor([-0.4615,  2.6124])\n",
      "\tparams: tensor([ 2.6557, -1.9526])\n",
      "Epoch: 79,Loss: 23.571455\n",
      "\tgrad: tensor([-0.4607,  2.6080])\n",
      "\tparams: tensor([ 2.6603, -1.9787])\n",
      "Epoch: 80,Loss: 23.501379\n",
      "\tgrad: tensor([-0.4599,  2.6035])\n",
      "\tparams: tensor([ 2.6649, -2.0047])\n",
      "Epoch: 81,Loss: 23.431538\n",
      "\tgrad: tensor([-0.4591,  2.5991])\n",
      "\tparams: tensor([ 2.6695, -2.0307])\n",
      "Epoch: 82,Loss: 23.361937\n",
      "\tgrad: tensor([-0.4584,  2.5947])\n",
      "\tparams: tensor([ 2.6741, -2.0566])\n",
      "Epoch: 83,Loss: 23.292570\n",
      "\tgrad: tensor([-0.4576,  2.5903])\n",
      "\tparams: tensor([ 2.6787, -2.0825])\n",
      "Epoch: 84,Loss: 23.223436\n",
      "\tgrad: tensor([-0.4568,  2.5859])\n",
      "\tparams: tensor([ 2.6832, -2.1084])\n",
      "Epoch: 85,Loss: 23.154541\n",
      "\tgrad: tensor([-0.4560,  2.5815])\n",
      "\tparams: tensor([ 2.6878, -2.1342])\n",
      "Epoch: 86,Loss: 23.085882\n",
      "\tgrad: tensor([-0.4553,  2.5771])\n",
      "\tparams: tensor([ 2.6923, -2.1600])\n",
      "Epoch: 87,Loss: 23.017447\n",
      "\tgrad: tensor([-0.4545,  2.5727])\n",
      "\tparams: tensor([ 2.6969, -2.1857])\n",
      "Epoch: 88,Loss: 22.949251\n",
      "\tgrad: tensor([-0.4537,  2.5684])\n",
      "\tparams: tensor([ 2.7014, -2.2114])\n",
      "Epoch: 89,Loss: 22.881283\n",
      "\tgrad: tensor([-0.4529,  2.5640])\n",
      "\tparams: tensor([ 2.7060, -2.2370])\n",
      "Epoch: 90,Loss: 22.813549\n",
      "\tgrad: tensor([-0.4522,  2.5597])\n",
      "\tparams: tensor([ 2.7105, -2.2626])\n",
      "Epoch: 91,Loss: 22.746044\n",
      "\tgrad: tensor([-0.4514,  2.5553])\n",
      "\tparams: tensor([ 2.7150, -2.2882])\n",
      "Epoch: 92,Loss: 22.678766\n",
      "\tgrad: tensor([-0.4506,  2.5510])\n",
      "\tparams: tensor([ 2.7195, -2.3137])\n",
      "Epoch: 93,Loss: 22.611717\n",
      "\tgrad: tensor([-0.4499,  2.5466])\n",
      "\tparams: tensor([ 2.7240, -2.3392])\n",
      "Epoch: 94,Loss: 22.544899\n",
      "\tgrad: tensor([-0.4491,  2.5423])\n",
      "\tparams: tensor([ 2.7285, -2.3646])\n",
      "Epoch: 95,Loss: 22.478306\n",
      "\tgrad: tensor([-0.4483,  2.5380])\n",
      "\tparams: tensor([ 2.7330, -2.3900])\n",
      "Epoch: 96,Loss: 22.411934\n",
      "\tgrad: tensor([-0.4476,  2.5337])\n",
      "\tparams: tensor([ 2.7374, -2.4153])\n",
      "Epoch: 97,Loss: 22.345793\n",
      "\tgrad: tensor([-0.4468,  2.5294])\n",
      "\tparams: tensor([ 2.7419, -2.4406])\n",
      "Epoch: 98,Loss: 22.279875\n",
      "\tgrad: tensor([-0.4461,  2.5251])\n",
      "\tparams: tensor([ 2.7464, -2.4658])\n",
      "Epoch: 99,Loss: 22.214186\n",
      "\tgrad: tensor([-0.4453,  2.5208])\n",
      "\tparams: tensor([ 2.7508, -2.4910])\n",
      "Epoch: 100,Loss: 22.148710\n",
      "\tgrad: tensor([-0.4446,  2.5165])\n",
      "\tparams: tensor([ 2.7553, -2.5162])\n",
      "Epoch: 101,Loss: 22.083464\n",
      "\tgrad: tensor([-0.4438,  2.5122])\n",
      "\tparams: tensor([ 2.7597, -2.5413])\n",
      "Epoch: 102,Loss: 22.018436\n",
      "\tgrad: tensor([-0.4430,  2.5080])\n",
      "\tparams: tensor([ 2.7641, -2.5664])\n",
      "Epoch: 103,Loss: 21.953632\n",
      "\tgrad: tensor([-0.4423,  2.5037])\n",
      "\tparams: tensor([ 2.7686, -2.5914])\n",
      "Epoch: 104,Loss: 21.889046\n",
      "\tgrad: tensor([-0.4415,  2.4994])\n",
      "\tparams: tensor([ 2.7730, -2.6164])\n",
      "Epoch: 105,Loss: 21.824677\n",
      "\tgrad: tensor([-0.4408,  2.4952])\n",
      "\tparams: tensor([ 2.7774, -2.6414])\n",
      "Epoch: 106,Loss: 21.760529\n",
      "\tgrad: tensor([-0.4400,  2.4910])\n",
      "\tparams: tensor([ 2.7818, -2.6663])\n",
      "Epoch: 107,Loss: 21.696600\n",
      "\tgrad: tensor([-0.4393,  2.4867])\n",
      "\tparams: tensor([ 2.7862, -2.6912])\n",
      "Epoch: 108,Loss: 21.632883\n",
      "\tgrad: tensor([-0.4385,  2.4825])\n",
      "\tparams: tensor([ 2.7906, -2.7160])\n",
      "Epoch: 109,Loss: 21.569389\n",
      "\tgrad: tensor([-0.4378,  2.4783])\n",
      "\tparams: tensor([ 2.7949, -2.7408])\n",
      "Epoch: 110,Loss: 21.506102\n",
      "\tgrad: tensor([-0.4370,  2.4741])\n",
      "\tparams: tensor([ 2.7993, -2.7655])\n",
      "Epoch: 111,Loss: 21.443037\n",
      "\tgrad: tensor([-0.4363,  2.4699])\n",
      "\tparams: tensor([ 2.8037, -2.7902])\n",
      "Epoch: 112,Loss: 21.380186\n",
      "\tgrad: tensor([-0.4356,  2.4657])\n",
      "\tparams: tensor([ 2.8080, -2.8149])\n",
      "Epoch: 113,Loss: 21.317549\n",
      "\tgrad: tensor([-0.4348,  2.4615])\n",
      "\tparams: tensor([ 2.8124, -2.8395])\n",
      "Epoch: 114,Loss: 21.255117\n",
      "\tgrad: tensor([-0.4341,  2.4573])\n",
      "\tparams: tensor([ 2.8167, -2.8641])\n",
      "Epoch: 115,Loss: 21.192907\n",
      "\tgrad: tensor([-0.4334,  2.4531])\n",
      "\tparams: tensor([ 2.8211, -2.8886])\n",
      "Epoch: 116,Loss: 21.130898\n",
      "\tgrad: tensor([-0.4326,  2.4490])\n",
      "\tparams: tensor([ 2.8254, -2.9131])\n",
      "Epoch: 117,Loss: 21.069105\n",
      "\tgrad: tensor([-0.4319,  2.4448])\n",
      "\tparams: tensor([ 2.8297, -2.9375])\n",
      "Epoch: 118,Loss: 21.007526\n",
      "\tgrad: tensor([-0.4311,  2.4407])\n",
      "\tparams: tensor([ 2.8340, -2.9619])\n",
      "Epoch: 119,Loss: 20.946150\n",
      "\tgrad: tensor([-0.4304,  2.4365])\n",
      "\tparams: tensor([ 2.8383, -2.9863])\n",
      "Epoch: 120,Loss: 20.884981\n",
      "\tgrad: tensor([-0.4297,  2.4324])\n",
      "\tparams: tensor([ 2.8426, -3.0106])\n",
      "Epoch: 121,Loss: 20.824024\n",
      "\tgrad: tensor([-0.4290,  2.4282])\n",
      "\tparams: tensor([ 2.8469, -3.0349])\n",
      "Epoch: 122,Loss: 20.763273\n",
      "\tgrad: tensor([-0.4282,  2.4241])\n",
      "\tparams: tensor([ 2.8512, -3.0592])\n",
      "Epoch: 123,Loss: 20.702728\n",
      "\tgrad: tensor([-0.4275,  2.4200])\n",
      "\tparams: tensor([ 2.8555, -3.0834])\n",
      "Epoch: 124,Loss: 20.642384\n",
      "\tgrad: tensor([-0.4268,  2.4159])\n",
      "\tparams: tensor([ 2.8597, -3.1075])\n",
      "Epoch: 125,Loss: 20.582249\n",
      "\tgrad: tensor([-0.4260,  2.4118])\n",
      "\tparams: tensor([ 2.8640, -3.1316])\n",
      "Epoch: 126,Loss: 20.522322\n",
      "\tgrad: tensor([-0.4253,  2.4077])\n",
      "\tparams: tensor([ 2.8682, -3.1557])\n",
      "Epoch: 127,Loss: 20.462593\n",
      "\tgrad: tensor([-0.4246,  2.4036])\n",
      "\tparams: tensor([ 2.8725, -3.1797])\n",
      "Epoch: 128,Loss: 20.403069\n",
      "\tgrad: tensor([-0.4239,  2.3995])\n",
      "\tparams: tensor([ 2.8767, -3.2037])\n",
      "Epoch: 129,Loss: 20.343742\n",
      "\tgrad: tensor([-0.4232,  2.3954])\n",
      "\tparams: tensor([ 2.8810, -3.2277])\n",
      "Epoch: 130,Loss: 20.284624\n",
      "\tgrad: tensor([-0.4224,  2.3914])\n",
      "\tparams: tensor([ 2.8852, -3.2516])\n",
      "Epoch: 131,Loss: 20.225702\n",
      "\tgrad: tensor([-0.4217,  2.3873])\n",
      "\tparams: tensor([ 2.8894, -3.2755])\n",
      "Epoch: 132,Loss: 20.166981\n",
      "\tgrad: tensor([-0.4210,  2.3832])\n",
      "\tparams: tensor([ 2.8936, -3.2993])\n",
      "Epoch: 133,Loss: 20.108461\n",
      "\tgrad: tensor([-0.4203,  2.3792])\n",
      "\tparams: tensor([ 2.8978, -3.3231])\n",
      "Epoch: 134,Loss: 20.050137\n",
      "\tgrad: tensor([-0.4196,  2.3752])\n",
      "\tparams: tensor([ 2.9020, -3.3469])\n",
      "Epoch: 135,Loss: 19.992016\n",
      "\tgrad: tensor([-0.4189,  2.3711])\n",
      "\tparams: tensor([ 2.9062, -3.3706])\n",
      "Epoch: 136,Loss: 19.934086\n",
      "\tgrad: tensor([-0.4182,  2.3671])\n",
      "\tparams: tensor([ 2.9104, -3.3942])\n",
      "Epoch: 137,Loss: 19.876352\n",
      "\tgrad: tensor([-0.4174,  2.3631])\n",
      "\tparams: tensor([ 2.9146, -3.4179])\n",
      "Epoch: 138,Loss: 19.818823\n",
      "\tgrad: tensor([-0.4167,  2.3591])\n",
      "\tparams: tensor([ 2.9187, -3.4415])\n",
      "Epoch: 139,Loss: 19.761480\n",
      "\tgrad: tensor([-0.4160,  2.3550])\n",
      "\tparams: tensor([ 2.9229, -3.4650])\n",
      "Epoch: 140,Loss: 19.704336\n",
      "\tgrad: tensor([-0.4153,  2.3510])\n",
      "\tparams: tensor([ 2.9270, -3.4885])\n",
      "Epoch: 141,Loss: 19.647385\n",
      "\tgrad: tensor([-0.4146,  2.3471])\n",
      "\tparams: tensor([ 2.9312, -3.5120])\n",
      "Epoch: 142,Loss: 19.590626\n",
      "\tgrad: tensor([-0.4139,  2.3431])\n",
      "\tparams: tensor([ 2.9353, -3.5354])\n",
      "Epoch: 143,Loss: 19.534061\n",
      "\tgrad: tensor([-0.4132,  2.3391])\n",
      "\tparams: tensor([ 2.9395, -3.5588])\n",
      "Epoch: 144,Loss: 19.477690\n",
      "\tgrad: tensor([-0.4125,  2.3351])\n",
      "\tparams: tensor([ 2.9436, -3.5822])\n",
      "Epoch: 145,Loss: 19.421507\n",
      "\tgrad: tensor([-0.4118,  2.3311])\n",
      "\tparams: tensor([ 2.9477, -3.6055])\n",
      "Epoch: 146,Loss: 19.365515\n",
      "\tgrad: tensor([-0.4111,  2.3272])\n",
      "\tparams: tensor([ 2.9518, -3.6287])\n",
      "Epoch: 147,Loss: 19.309715\n",
      "\tgrad: tensor([-0.4104,  2.3232])\n",
      "\tparams: tensor([ 2.9559, -3.6520])\n",
      "Epoch: 148,Loss: 19.254107\n",
      "\tgrad: tensor([-0.4097,  2.3193])\n",
      "\tparams: tensor([ 2.9600, -3.6752])\n",
      "Epoch: 149,Loss: 19.198685\n",
      "\tgrad: tensor([-0.4090,  2.3153])\n",
      "\tparams: tensor([ 2.9641, -3.6983])\n",
      "Epoch: 150,Loss: 19.143446\n",
      "\tgrad: tensor([-0.4083,  2.3114])\n",
      "\tparams: tensor([ 2.9682, -3.7214])\n",
      "Epoch: 151,Loss: 19.088402\n",
      "\tgrad: tensor([-0.4076,  2.3075])\n",
      "\tparams: tensor([ 2.9723, -3.7445])\n",
      "Epoch: 152,Loss: 19.033543\n",
      "\tgrad: tensor([-0.4069,  2.3036])\n",
      "\tparams: tensor([ 2.9763, -3.7675])\n",
      "Epoch: 153,Loss: 18.978868\n",
      "\tgrad: tensor([-0.4062,  2.2997])\n",
      "\tparams: tensor([ 2.9804, -3.7905])\n",
      "Epoch: 154,Loss: 18.924377\n",
      "\tgrad: tensor([-0.4056,  2.2957])\n",
      "\tparams: tensor([ 2.9844, -3.8135])\n",
      "Epoch: 155,Loss: 18.870081\n",
      "\tgrad: tensor([-0.4049,  2.2918])\n",
      "\tparams: tensor([ 2.9885, -3.8364])\n",
      "Epoch: 156,Loss: 18.815960\n",
      "\tgrad: tensor([-0.4042,  2.2880])\n",
      "\tparams: tensor([ 2.9925, -3.8593])\n",
      "Epoch: 157,Loss: 18.762022\n",
      "\tgrad: tensor([-0.4035,  2.2841])\n",
      "\tparams: tensor([ 2.9966, -3.8821])\n",
      "Epoch: 158,Loss: 18.708271\n",
      "\tgrad: tensor([-0.4028,  2.2802])\n",
      "\tparams: tensor([ 3.0006, -3.9049])\n",
      "Epoch: 159,Loss: 18.654699\n",
      "\tgrad: tensor([-0.4021,  2.2763])\n",
      "\tparams: tensor([ 3.0046, -3.9277])\n",
      "Epoch: 160,Loss: 18.601313\n",
      "\tgrad: tensor([-0.4014,  2.2724])\n",
      "\tparams: tensor([ 3.0086, -3.9504])\n",
      "Epoch: 161,Loss: 18.548109\n",
      "\tgrad: tensor([-0.4007,  2.2686])\n",
      "\tparams: tensor([ 3.0126, -3.9731])\n",
      "Epoch: 162,Loss: 18.495085\n",
      "\tgrad: tensor([-0.4001,  2.2647])\n",
      "\tparams: tensor([ 3.0166, -3.9958])\n",
      "Epoch: 163,Loss: 18.442236\n",
      "\tgrad: tensor([-0.3994,  2.2609])\n",
      "\tparams: tensor([ 3.0206, -4.0184])\n",
      "Epoch: 164,Loss: 18.389570\n",
      "\tgrad: tensor([-0.3987,  2.2570])\n",
      "\tparams: tensor([ 3.0246, -4.0409])\n",
      "Epoch: 165,Loss: 18.337080\n",
      "\tgrad: tensor([-0.3980,  2.2532])\n",
      "\tparams: tensor([ 3.0286, -4.0635])\n",
      "Epoch: 166,Loss: 18.284777\n",
      "\tgrad: tensor([-0.3974,  2.2494])\n",
      "\tparams: tensor([ 3.0326, -4.0860])\n",
      "Epoch: 167,Loss: 18.232641\n",
      "\tgrad: tensor([-0.3967,  2.2456])\n",
      "\tparams: tensor([ 3.0365, -4.1084])\n",
      "Epoch: 168,Loss: 18.180685\n",
      "\tgrad: tensor([-0.3960,  2.2417])\n",
      "\tparams: tensor([ 3.0405, -4.1308])\n",
      "Epoch: 169,Loss: 18.128906\n",
      "\tgrad: tensor([-0.3953,  2.2379])\n",
      "\tparams: tensor([ 3.0445, -4.1532])\n",
      "Epoch: 170,Loss: 18.077301\n",
      "\tgrad: tensor([-0.3947,  2.2341])\n",
      "\tparams: tensor([ 3.0484, -4.1756])\n",
      "Epoch: 171,Loss: 18.025877\n",
      "\tgrad: tensor([-0.3940,  2.2303])\n",
      "\tparams: tensor([ 3.0523, -4.1979])\n",
      "Epoch: 172,Loss: 17.974623\n",
      "\tgrad: tensor([-0.3933,  2.2266])\n",
      "\tparams: tensor([ 3.0563, -4.2201])\n",
      "Epoch: 173,Loss: 17.923546\n",
      "\tgrad: tensor([-0.3927,  2.2228])\n",
      "\tparams: tensor([ 3.0602, -4.2424])\n",
      "Epoch: 174,Loss: 17.872643\n",
      "\tgrad: tensor([-0.3920,  2.2190])\n",
      "\tparams: tensor([ 3.0641, -4.2646])\n",
      "Epoch: 175,Loss: 17.821909\n",
      "\tgrad: tensor([-0.3913,  2.2152])\n",
      "\tparams: tensor([ 3.0680, -4.2867])\n",
      "Epoch: 176,Loss: 17.771345\n",
      "\tgrad: tensor([-0.3907,  2.2115])\n",
      "\tparams: tensor([ 3.0719, -4.3088])\n",
      "Epoch: 177,Loss: 17.720955\n",
      "\tgrad: tensor([-0.3900,  2.2077])\n",
      "\tparams: tensor([ 3.0758, -4.3309])\n",
      "Epoch: 178,Loss: 17.670738\n",
      "\tgrad: tensor([-0.3893,  2.2040])\n",
      "\tparams: tensor([ 3.0797, -4.3529])\n",
      "Epoch: 179,Loss: 17.620689\n",
      "\tgrad: tensor([-0.3887,  2.2002])\n",
      "\tparams: tensor([ 3.0836, -4.3749])\n",
      "Epoch: 180,Loss: 17.570814\n",
      "\tgrad: tensor([-0.3880,  2.1965])\n",
      "\tparams: tensor([ 3.0875, -4.3969])\n",
      "Epoch: 181,Loss: 17.521103\n",
      "\tgrad: tensor([-0.3873,  2.1927])\n",
      "\tparams: tensor([ 3.0914, -4.4188])\n",
      "Epoch: 182,Loss: 17.471565\n",
      "\tgrad: tensor([-0.3867,  2.1890])\n",
      "\tparams: tensor([ 3.0952, -4.4407])\n",
      "Epoch: 183,Loss: 17.422192\n",
      "\tgrad: tensor([-0.3860,  2.1853])\n",
      "\tparams: tensor([ 3.0991, -4.4626])\n",
      "Epoch: 184,Loss: 17.372993\n",
      "\tgrad: tensor([-0.3854,  2.1816])\n",
      "\tparams: tensor([ 3.1030, -4.4844])\n",
      "Epoch: 185,Loss: 17.323954\n",
      "\tgrad: tensor([-0.3847,  2.1779])\n",
      "\tparams: tensor([ 3.1068, -4.5062])\n",
      "Epoch: 186,Loss: 17.275084\n",
      "\tgrad: tensor([-0.3841,  2.1742])\n",
      "\tparams: tensor([ 3.1106, -4.5279])\n",
      "Epoch: 187,Loss: 17.226379\n",
      "\tgrad: tensor([-0.3834,  2.1705])\n",
      "\tparams: tensor([ 3.1145, -4.5496])\n",
      "Epoch: 188,Loss: 17.177839\n",
      "\tgrad: tensor([-0.3828,  2.1668])\n",
      "\tparams: tensor([ 3.1183, -4.5713])\n",
      "Epoch: 189,Loss: 17.129463\n",
      "\tgrad: tensor([-0.3821,  2.1631])\n",
      "\tparams: tensor([ 3.1221, -4.5929])\n",
      "Epoch: 190,Loss: 17.081255\n",
      "\tgrad: tensor([-0.3815,  2.1594])\n",
      "\tparams: tensor([ 3.1259, -4.6145])\n",
      "Epoch: 191,Loss: 17.033209\n",
      "\tgrad: tensor([-0.3808,  2.1558])\n",
      "\tparams: tensor([ 3.1298, -4.6361])\n",
      "Epoch: 192,Loss: 16.985327\n",
      "\tgrad: tensor([-0.3802,  2.1521])\n",
      "\tparams: tensor([ 3.1336, -4.6576])\n",
      "Epoch: 193,Loss: 16.937605\n",
      "\tgrad: tensor([-0.3795,  2.1485])\n",
      "\tparams: tensor([ 3.1374, -4.6791])\n",
      "Epoch: 194,Loss: 16.890047\n",
      "\tgrad: tensor([-0.3789,  2.1448])\n",
      "\tparams: tensor([ 3.1411, -4.7005])\n",
      "Epoch: 195,Loss: 16.842649\n",
      "\tgrad: tensor([-0.3782,  2.1412])\n",
      "\tparams: tensor([ 3.1449, -4.7219])\n",
      "Epoch: 196,Loss: 16.795412\n",
      "\tgrad: tensor([-0.3776,  2.1375])\n",
      "\tparams: tensor([ 3.1487, -4.7433])\n",
      "Epoch: 197,Loss: 16.748339\n",
      "\tgrad: tensor([-0.3770,  2.1339])\n",
      "\tparams: tensor([ 3.1525, -4.7646])\n",
      "Epoch: 198,Loss: 16.701422\n",
      "\tgrad: tensor([-0.3763,  2.1303])\n",
      "\tparams: tensor([ 3.1562, -4.7859])\n",
      "Epoch: 199,Loss: 16.654661\n",
      "\tgrad: tensor([-0.3757,  2.1267])\n",
      "\tparams: tensor([ 3.1600, -4.8072])\n",
      "Epoch: 200,Loss: 16.608067\n",
      "\tgrad: tensor([-0.3750,  2.1230])\n",
      "\tparams: tensor([ 3.1637, -4.8284])\n",
      "Epoch: 201,Loss: 16.561623\n",
      "\tgrad: tensor([-0.3744,  2.1194])\n",
      "\tparams: tensor([ 3.1675, -4.8496])\n",
      "Epoch: 202,Loss: 16.515343\n",
      "\tgrad: tensor([-0.3738,  2.1158])\n",
      "\tparams: tensor([ 3.1712, -4.8708])\n",
      "Epoch: 203,Loss: 16.469219\n",
      "\tgrad: tensor([-0.3731,  2.1122])\n",
      "\tparams: tensor([ 3.1750, -4.8919])\n",
      "Epoch: 204,Loss: 16.423248\n",
      "\tgrad: tensor([-0.3725,  2.1087])\n",
      "\tparams: tensor([ 3.1787, -4.9130])\n",
      "Epoch: 205,Loss: 16.377434\n",
      "\tgrad: tensor([-0.3719,  2.1051])\n",
      "\tparams: tensor([ 3.1824, -4.9341])\n",
      "Epoch: 206,Loss: 16.331776\n",
      "\tgrad: tensor([-0.3712,  2.1015])\n",
      "\tparams: tensor([ 3.1861, -4.9551])\n",
      "Epoch: 207,Loss: 16.286276\n",
      "\tgrad: tensor([-0.3706,  2.0979])\n",
      "\tparams: tensor([ 3.1898, -4.9760])\n",
      "Epoch: 208,Loss: 16.240929\n",
      "\tgrad: tensor([-0.3700,  2.0944])\n",
      "\tparams: tensor([ 3.1935, -4.9970])\n",
      "Epoch: 209,Loss: 16.195732\n",
      "\tgrad: tensor([-0.3694,  2.0908])\n",
      "\tparams: tensor([ 3.1972, -5.0179])\n",
      "Epoch: 210,Loss: 16.150694\n",
      "\tgrad: tensor([-0.3687,  2.0873])\n",
      "\tparams: tensor([ 3.2009, -5.0388])\n",
      "Epoch: 211,Loss: 16.105806\n",
      "\tgrad: tensor([-0.3681,  2.0837])\n",
      "\tparams: tensor([ 3.2046, -5.0596])\n",
      "Epoch: 212,Loss: 16.061073\n",
      "\tgrad: tensor([-0.3675,  2.0802])\n",
      "\tparams: tensor([ 3.2082, -5.0804])\n",
      "Epoch: 213,Loss: 16.016487\n",
      "\tgrad: tensor([-0.3668,  2.0766])\n",
      "\tparams: tensor([ 3.2119, -5.1012])\n",
      "Epoch: 214,Loss: 15.972058\n",
      "\tgrad: tensor([-0.3662,  2.0731])\n",
      "\tparams: tensor([ 3.2156, -5.1219])\n",
      "Epoch: 215,Loss: 15.927776\n",
      "\tgrad: tensor([-0.3656,  2.0696])\n",
      "\tparams: tensor([ 3.2192, -5.1426])\n",
      "Epoch: 216,Loss: 15.883645\n",
      "\tgrad: tensor([-0.3650,  2.0661])\n",
      "\tparams: tensor([ 3.2229, -5.1633])\n",
      "Epoch: 217,Loss: 15.839664\n",
      "\tgrad: tensor([-0.3644,  2.0626])\n",
      "\tparams: tensor([ 3.2265, -5.1839])\n",
      "Epoch: 218,Loss: 15.795832\n",
      "\tgrad: tensor([-0.3637,  2.0591])\n",
      "\tparams: tensor([ 3.2302, -5.2045])\n",
      "Epoch: 219,Loss: 15.752152\n",
      "\tgrad: tensor([-0.3631,  2.0556])\n",
      "\tparams: tensor([ 3.2338, -5.2250])\n",
      "Epoch: 220,Loss: 15.708612\n",
      "\tgrad: tensor([-0.3625,  2.0521])\n",
      "\tparams: tensor([ 3.2374, -5.2456])\n",
      "Epoch: 221,Loss: 15.665226\n",
      "\tgrad: tensor([-0.3619,  2.0486])\n",
      "\tparams: tensor([ 3.2410, -5.2660])\n",
      "Epoch: 222,Loss: 15.621990\n",
      "\tgrad: tensor([-0.3613,  2.0451])\n",
      "\tparams: tensor([ 3.2447, -5.2865])\n",
      "Epoch: 223,Loss: 15.578897\n",
      "\tgrad: tensor([-0.3607,  2.0416])\n",
      "\tparams: tensor([ 3.2483, -5.3069])\n",
      "Epoch: 224,Loss: 15.535950\n",
      "\tgrad: tensor([-0.3601,  2.0382])\n",
      "\tparams: tensor([ 3.2519, -5.3273])\n",
      "Epoch: 225,Loss: 15.493150\n",
      "\tgrad: tensor([-0.3594,  2.0347])\n",
      "\tparams: tensor([ 3.2555, -5.3476])\n",
      "Epoch: 226,Loss: 15.450495\n",
      "\tgrad: tensor([-0.3588,  2.0312])\n",
      "\tparams: tensor([ 3.2590, -5.3680])\n",
      "Epoch: 227,Loss: 15.407981\n",
      "\tgrad: tensor([-0.3582,  2.0278])\n",
      "\tparams: tensor([ 3.2626, -5.3882])\n",
      "Epoch: 228,Loss: 15.365616\n",
      "\tgrad: tensor([-0.3576,  2.0243])\n",
      "\tparams: tensor([ 3.2662, -5.4085])\n",
      "Epoch: 229,Loss: 15.323396\n",
      "\tgrad: tensor([-0.3570,  2.0209])\n",
      "\tparams: tensor([ 3.2698, -5.4287])\n",
      "Epoch: 230,Loss: 15.281317\n",
      "\tgrad: tensor([-0.3564,  2.0175])\n",
      "\tparams: tensor([ 3.2733, -5.4489])\n",
      "Epoch: 231,Loss: 15.239380\n",
      "\tgrad: tensor([-0.3558,  2.0140])\n",
      "\tparams: tensor([ 3.2769, -5.4690])\n",
      "Epoch: 232,Loss: 15.197585\n",
      "\tgrad: tensor([-0.3552,  2.0106])\n",
      "\tparams: tensor([ 3.2804, -5.4891])\n",
      "Epoch: 233,Loss: 15.155932\n",
      "\tgrad: tensor([-0.3546,  2.0072])\n",
      "\tparams: tensor([ 3.2840, -5.5092])\n",
      "Epoch: 234,Loss: 15.114425\n",
      "\tgrad: tensor([-0.3540,  2.0038])\n",
      "\tparams: tensor([ 3.2875, -5.5292])\n",
      "Epoch: 235,Loss: 15.073055\n",
      "\tgrad: tensor([-0.3534,  2.0004])\n",
      "\tparams: tensor([ 3.2911, -5.5492])\n",
      "Epoch: 236,Loss: 15.031823\n",
      "\tgrad: tensor([-0.3528,  1.9970])\n",
      "\tparams: tensor([ 3.2946, -5.5692])\n",
      "Epoch: 237,Loss: 14.990734\n",
      "\tgrad: tensor([-0.3522,  1.9936])\n",
      "\tparams: tensor([ 3.2981, -5.5891])\n",
      "Epoch: 238,Loss: 14.949784\n",
      "\tgrad: tensor([-0.3516,  1.9902])\n",
      "\tparams: tensor([ 3.3016, -5.6090])\n",
      "Epoch: 239,Loss: 14.908973\n",
      "\tgrad: tensor([-0.3510,  1.9868])\n",
      "\tparams: tensor([ 3.3051, -5.6289])\n",
      "Epoch: 240,Loss: 14.868304\n",
      "\tgrad: tensor([-0.3504,  1.9835])\n",
      "\tparams: tensor([ 3.3086, -5.6487])\n",
      "Epoch: 241,Loss: 14.827767\n",
      "\tgrad: tensor([-0.3498,  1.9801])\n",
      "\tparams: tensor([ 3.3121, -5.6685])\n",
      "Epoch: 242,Loss: 14.787370\n",
      "\tgrad: tensor([-0.3492,  1.9767])\n",
      "\tparams: tensor([ 3.3156, -5.6883])\n",
      "Epoch: 243,Loss: 14.747109\n",
      "\tgrad: tensor([-0.3486,  1.9734])\n",
      "\tparams: tensor([ 3.3191, -5.7080])\n",
      "Epoch: 244,Loss: 14.706989\n",
      "\tgrad: tensor([-0.3480,  1.9700])\n",
      "\tparams: tensor([ 3.3226, -5.7277])\n",
      "Epoch: 245,Loss: 14.667002\n",
      "\tgrad: tensor([-0.3474,  1.9667])\n",
      "\tparams: tensor([ 3.3261, -5.7474])\n",
      "Epoch: 246,Loss: 14.627151\n",
      "\tgrad: tensor([-0.3468,  1.9633])\n",
      "\tparams: tensor([ 3.3295, -5.7670])\n",
      "Epoch: 247,Loss: 14.587436\n",
      "\tgrad: tensor([-0.3462,  1.9600])\n",
      "\tparams: tensor([ 3.3330, -5.7866])\n",
      "Epoch: 248,Loss: 14.547855\n",
      "\tgrad: tensor([-0.3456,  1.9567])\n",
      "\tparams: tensor([ 3.3365, -5.8062])\n",
      "Epoch: 249,Loss: 14.508409\n",
      "\tgrad: tensor([-0.3451,  1.9533])\n",
      "\tparams: tensor([ 3.3399, -5.8257])\n",
      "Epoch: 250,Loss: 14.469097\n",
      "\tgrad: tensor([-0.3445,  1.9500])\n",
      "\tparams: tensor([ 3.3434, -5.8452])\n",
      "Epoch: 251,Loss: 14.429920\n",
      "\tgrad: tensor([-0.3439,  1.9467])\n",
      "\tparams: tensor([ 3.3468, -5.8647])\n",
      "Epoch: 252,Loss: 14.390870\n",
      "\tgrad: tensor([-0.3433,  1.9434])\n",
      "\tparams: tensor([ 3.3502, -5.8841])\n",
      "Epoch: 253,Loss: 14.351956\n",
      "\tgrad: tensor([-0.3427,  1.9401])\n",
      "\tparams: tensor([ 3.3537, -5.9035])\n",
      "Epoch: 254,Loss: 14.313177\n",
      "\tgrad: tensor([-0.3421,  1.9368])\n",
      "\tparams: tensor([ 3.3571, -5.9229])\n",
      "Epoch: 255,Loss: 14.274529\n",
      "\tgrad: tensor([-0.3416,  1.9335])\n",
      "\tparams: tensor([ 3.3605, -5.9422])\n",
      "Epoch: 256,Loss: 14.236009\n",
      "\tgrad: tensor([-0.3410,  1.9302])\n",
      "\tparams: tensor([ 3.3639, -5.9615])\n",
      "Epoch: 257,Loss: 14.197620\n",
      "\tgrad: tensor([-0.3404,  1.9269])\n",
      "\tparams: tensor([ 3.3673, -5.9808])\n",
      "Epoch: 258,Loss: 14.159363\n",
      "\tgrad: tensor([-0.3398,  1.9237])\n",
      "\tparams: tensor([ 3.3707, -6.0000])\n",
      "Epoch: 259,Loss: 14.121234\n",
      "\tgrad: tensor([-0.3392,  1.9204])\n",
      "\tparams: tensor([ 3.3741, -6.0192])\n",
      "Epoch: 260,Loss: 14.083236\n",
      "\tgrad: tensor([-0.3387,  1.9171])\n",
      "\tparams: tensor([ 3.3775, -6.0384])\n",
      "Epoch: 261,Loss: 14.045367\n",
      "\tgrad: tensor([-0.3381,  1.9139])\n",
      "\tparams: tensor([ 3.3809, -6.0576])\n",
      "Epoch: 262,Loss: 14.007627\n",
      "\tgrad: tensor([-0.3375,  1.9106])\n",
      "\tparams: tensor([ 3.3842, -6.0767])\n",
      "Epoch: 263,Loss: 13.970016\n",
      "\tgrad: tensor([-0.3369,  1.9074])\n",
      "\tparams: tensor([ 3.3876, -6.0957])\n",
      "Epoch: 264,Loss: 13.932531\n",
      "\tgrad: tensor([-0.3364,  1.9041])\n",
      "\tparams: tensor([ 3.3910, -6.1148])\n",
      "Epoch: 265,Loss: 13.895172\n",
      "\tgrad: tensor([-0.3358,  1.9009])\n",
      "\tparams: tensor([ 3.3943, -6.1338])\n",
      "Epoch: 266,Loss: 13.857944\n",
      "\tgrad: tensor([-0.3352,  1.8977])\n",
      "\tparams: tensor([ 3.3977, -6.1528])\n",
      "Epoch: 267,Loss: 13.820837\n",
      "\tgrad: tensor([-0.3347,  1.8945])\n",
      "\tparams: tensor([ 3.4010, -6.1717])\n",
      "Epoch: 268,Loss: 13.783858\n",
      "\tgrad: tensor([-0.3341,  1.8912])\n",
      "\tparams: tensor([ 3.4044, -6.1906])\n",
      "Epoch: 269,Loss: 13.747006\n",
      "\tgrad: tensor([-0.3335,  1.8880])\n",
      "\tparams: tensor([ 3.4077, -6.2095])\n",
      "Epoch: 270,Loss: 13.710278\n",
      "\tgrad: tensor([-0.3330,  1.8848])\n",
      "\tparams: tensor([ 3.4110, -6.2284])\n",
      "Epoch: 271,Loss: 13.673676\n",
      "\tgrad: tensor([-0.3324,  1.8816])\n",
      "\tparams: tensor([ 3.4144, -6.2472])\n",
      "Epoch: 272,Loss: 13.637196\n",
      "\tgrad: tensor([-0.3318,  1.8784])\n",
      "\tparams: tensor([ 3.4177, -6.2660])\n",
      "Epoch: 273,Loss: 13.600842\n",
      "\tgrad: tensor([-0.3313,  1.8752])\n",
      "\tparams: tensor([ 3.4210, -6.2847])\n",
      "Epoch: 274,Loss: 13.564609\n",
      "\tgrad: tensor([-0.3307,  1.8720])\n",
      "\tparams: tensor([ 3.4243, -6.3034])\n",
      "Epoch: 275,Loss: 13.528501\n",
      "\tgrad: tensor([-0.3301,  1.8689])\n",
      "\tparams: tensor([ 3.4276, -6.3221])\n",
      "Epoch: 276,Loss: 13.492514\n",
      "\tgrad: tensor([-0.3296,  1.8657])\n",
      "\tparams: tensor([ 3.4309, -6.3408])\n",
      "Epoch: 277,Loss: 13.456651\n",
      "\tgrad: tensor([-0.3290,  1.8625])\n",
      "\tparams: tensor([ 3.4342, -6.3594])\n",
      "Epoch: 278,Loss: 13.420910\n",
      "\tgrad: tensor([-0.3285,  1.8594])\n",
      "\tparams: tensor([ 3.4375, -6.3780])\n",
      "Epoch: 279,Loss: 13.385287\n",
      "\tgrad: tensor([-0.3279,  1.8562])\n",
      "\tparams: tensor([ 3.4407, -6.3966])\n",
      "Epoch: 280,Loss: 13.349789\n",
      "\tgrad: tensor([-0.3274,  1.8530])\n",
      "\tparams: tensor([ 3.4440, -6.4151])\n",
      "Epoch: 281,Loss: 13.314407\n",
      "\tgrad: tensor([-0.3268,  1.8499])\n",
      "\tparams: tensor([ 3.4473, -6.4336])\n",
      "Epoch: 282,Loss: 13.279150\n",
      "\tgrad: tensor([-0.3262,  1.8468])\n",
      "\tparams: tensor([ 3.4506, -6.4520])\n",
      "Epoch: 283,Loss: 13.244009\n",
      "\tgrad: tensor([-0.3257,  1.8436])\n",
      "\tparams: tensor([ 3.4538, -6.4705])\n",
      "Epoch: 284,Loss: 13.208991\n",
      "\tgrad: tensor([-0.3251,  1.8405])\n",
      "\tparams: tensor([ 3.4571, -6.4889])\n",
      "Epoch: 285,Loss: 13.174088\n",
      "\tgrad: tensor([-0.3246,  1.8374])\n",
      "\tparams: tensor([ 3.4603, -6.5073])\n",
      "Epoch: 286,Loss: 13.139307\n",
      "\tgrad: tensor([-0.3240,  1.8342])\n",
      "\tparams: tensor([ 3.4635, -6.5256])\n",
      "Epoch: 287,Loss: 13.104639\n",
      "\tgrad: tensor([-0.3235,  1.8311])\n",
      "\tparams: tensor([ 3.4668, -6.5439])\n",
      "Epoch: 288,Loss: 13.070092\n",
      "\tgrad: tensor([-0.3229,  1.8280])\n",
      "\tparams: tensor([ 3.4700, -6.5622])\n",
      "Epoch: 289,Loss: 13.035664\n",
      "\tgrad: tensor([-0.3224,  1.8249])\n",
      "\tparams: tensor([ 3.4732, -6.5804])\n",
      "Epoch: 290,Loss: 13.001349\n",
      "\tgrad: tensor([-0.3218,  1.8218])\n",
      "\tparams: tensor([ 3.4765, -6.5987])\n",
      "Epoch: 291,Loss: 12.967152\n",
      "\tgrad: tensor([-0.3213,  1.8187])\n",
      "\tparams: tensor([ 3.4797, -6.6169])\n",
      "Epoch: 292,Loss: 12.933075\n",
      "\tgrad: tensor([-0.3207,  1.8156])\n",
      "\tparams: tensor([ 3.4829, -6.6350])\n",
      "Epoch: 293,Loss: 12.899109\n",
      "\tgrad: tensor([-0.3202,  1.8125])\n",
      "\tparams: tensor([ 3.4861, -6.6531])\n",
      "Epoch: 294,Loss: 12.865259\n",
      "\tgrad: tensor([-0.3196,  1.8095])\n",
      "\tparams: tensor([ 3.4893, -6.6712])\n",
      "Epoch: 295,Loss: 12.831525\n",
      "\tgrad: tensor([-0.3191,  1.8064])\n",
      "\tparams: tensor([ 3.4925, -6.6893])\n",
      "Epoch: 296,Loss: 12.797904\n",
      "\tgrad: tensor([-0.3186,  1.8033])\n",
      "\tparams: tensor([ 3.4956, -6.7073])\n",
      "Epoch: 297,Loss: 12.764399\n",
      "\tgrad: tensor([-0.3180,  1.8003])\n",
      "\tparams: tensor([ 3.4988, -6.7253])\n",
      "Epoch: 298,Loss: 12.731007\n",
      "\tgrad: tensor([-0.3175,  1.7972])\n",
      "\tparams: tensor([ 3.5020, -6.7433])\n",
      "Epoch: 299,Loss: 12.697727\n",
      "\tgrad: tensor([-0.3169,  1.7941])\n",
      "\tparams: tensor([ 3.5052, -6.7612])\n",
      "Epoch: 300,Loss: 12.664559\n",
      "\tgrad: tensor([-0.3164,  1.7911])\n",
      "\tparams: tensor([ 3.5083, -6.7792])\n",
      "Epoch: 301,Loss: 12.631507\n",
      "\tgrad: tensor([-0.3159,  1.7881])\n",
      "\tparams: tensor([ 3.5115, -6.7970])\n",
      "Epoch: 302,Loss: 12.598568\n",
      "\tgrad: tensor([-0.3153,  1.7850])\n",
      "\tparams: tensor([ 3.5146, -6.8149])\n",
      "Epoch: 303,Loss: 12.565738\n",
      "\tgrad: tensor([-0.3148,  1.7820])\n",
      "\tparams: tensor([ 3.5178, -6.8327])\n",
      "Epoch: 304,Loss: 12.533021\n",
      "\tgrad: tensor([-0.3143,  1.7790])\n",
      "\tparams: tensor([ 3.5209, -6.8505])\n",
      "Epoch: 305,Loss: 12.500413\n",
      "\tgrad: tensor([-0.3137,  1.7759])\n",
      "\tparams: tensor([ 3.5241, -6.8683])\n",
      "Epoch: 306,Loss: 12.467919\n",
      "\tgrad: tensor([-0.3132,  1.7729])\n",
      "\tparams: tensor([ 3.5272, -6.8860])\n",
      "Epoch: 307,Loss: 12.435532\n",
      "\tgrad: tensor([-0.3127,  1.7699])\n",
      "\tparams: tensor([ 3.5303, -6.9037])\n",
      "Epoch: 308,Loss: 12.403256\n",
      "\tgrad: tensor([-0.3121,  1.7669])\n",
      "\tparams: tensor([ 3.5335, -6.9213])\n",
      "Epoch: 309,Loss: 12.371090\n",
      "\tgrad: tensor([-0.3116,  1.7639])\n",
      "\tparams: tensor([ 3.5366, -6.9390])\n",
      "Epoch: 310,Loss: 12.339031\n",
      "\tgrad: tensor([-0.3111,  1.7609])\n",
      "\tparams: tensor([ 3.5397, -6.9566])\n",
      "Epoch: 311,Loss: 12.307082\n",
      "\tgrad: tensor([-0.3105,  1.7579])\n",
      "\tparams: tensor([ 3.5428, -6.9742])\n",
      "Epoch: 312,Loss: 12.275247\n",
      "\tgrad: tensor([-0.3100,  1.7549])\n",
      "\tparams: tensor([ 3.5459, -6.9917])\n",
      "Epoch: 313,Loss: 12.243509\n",
      "\tgrad: tensor([-0.3095,  1.7519])\n",
      "\tparams: tensor([ 3.5490, -7.0092])\n",
      "Epoch: 314,Loss: 12.211887\n",
      "\tgrad: tensor([-0.3090,  1.7490])\n",
      "\tparams: tensor([ 3.5521, -7.0267])\n",
      "Epoch: 315,Loss: 12.180370\n",
      "\tgrad: tensor([-0.3084,  1.7460])\n",
      "\tparams: tensor([ 3.5552, -7.0442])\n",
      "Epoch: 316,Loss: 12.148962\n",
      "\tgrad: tensor([-0.3079,  1.7430])\n",
      "\tparams: tensor([ 3.5582, -7.0616])\n",
      "Epoch: 317,Loss: 12.117657\n",
      "\tgrad: tensor([-0.3074,  1.7401])\n",
      "\tparams: tensor([ 3.5613, -7.0790])\n",
      "Epoch: 318,Loss: 12.086462\n",
      "\tgrad: tensor([-0.3069,  1.7371])\n",
      "\tparams: tensor([ 3.5644, -7.0964])\n",
      "Epoch: 319,Loss: 12.055373\n",
      "\tgrad: tensor([-0.3063,  1.7342])\n",
      "\tparams: tensor([ 3.5674, -7.1137])\n",
      "Epoch: 320,Loss: 12.024384\n",
      "\tgrad: tensor([-0.3058,  1.7312])\n",
      "\tparams: tensor([ 3.5705, -7.1310])\n",
      "Epoch: 321,Loss: 11.993508\n",
      "\tgrad: tensor([-0.3053,  1.7283])\n",
      "\tparams: tensor([ 3.5736, -7.1483])\n",
      "Epoch: 322,Loss: 11.962731\n",
      "\tgrad: tensor([-0.3048,  1.7253])\n",
      "\tparams: tensor([ 3.5766, -7.1656])\n",
      "Epoch: 323,Loss: 11.932056\n",
      "\tgrad: tensor([-0.3043,  1.7224])\n",
      "\tparams: tensor([ 3.5796, -7.1828])\n",
      "Epoch: 324,Loss: 11.901492\n",
      "\tgrad: tensor([-0.3037,  1.7195])\n",
      "\tparams: tensor([ 3.5827, -7.2000])\n",
      "Epoch: 325,Loss: 11.871029\n",
      "\tgrad: tensor([-0.3032,  1.7166])\n",
      "\tparams: tensor([ 3.5857, -7.2172])\n",
      "Epoch: 326,Loss: 11.840671\n",
      "\tgrad: tensor([-0.3027,  1.7136])\n",
      "\tparams: tensor([ 3.5887, -7.2343])\n",
      "Epoch: 327,Loss: 11.810413\n",
      "\tgrad: tensor([-0.3022,  1.7107])\n",
      "\tparams: tensor([ 3.5918, -7.2514])\n",
      "Epoch: 328,Loss: 11.780257\n",
      "\tgrad: tensor([-0.3017,  1.7078])\n",
      "\tparams: tensor([ 3.5948, -7.2685])\n",
      "Epoch: 329,Loss: 11.750208\n",
      "\tgrad: tensor([-0.3012,  1.7049])\n",
      "\tparams: tensor([ 3.5978, -7.2855])\n",
      "Epoch: 330,Loss: 11.720258\n",
      "\tgrad: tensor([-0.3007,  1.7020])\n",
      "\tparams: tensor([ 3.6008, -7.3026])\n",
      "Epoch: 331,Loss: 11.690412\n",
      "\tgrad: tensor([-0.3002,  1.6991])\n",
      "\tparams: tensor([ 3.6038, -7.3196])\n",
      "Epoch: 332,Loss: 11.660664\n",
      "\tgrad: tensor([-0.2996,  1.6963])\n",
      "\tparams: tensor([ 3.6068, -7.3365])\n",
      "Epoch: 333,Loss: 11.631015\n",
      "\tgrad: tensor([-0.2991,  1.6934])\n",
      "\tparams: tensor([ 3.6098, -7.3535])\n",
      "Epoch: 334,Loss: 11.601473\n",
      "\tgrad: tensor([-0.2986,  1.6905])\n",
      "\tparams: tensor([ 3.6128, -7.3704])\n",
      "Epoch: 335,Loss: 11.572030\n",
      "\tgrad: tensor([-0.2981,  1.6876])\n",
      "\tparams: tensor([ 3.6158, -7.3872])\n",
      "Epoch: 336,Loss: 11.542686\n",
      "\tgrad: tensor([-0.2976,  1.6848])\n",
      "\tparams: tensor([ 3.6187, -7.4041])\n",
      "Epoch: 337,Loss: 11.513440\n",
      "\tgrad: tensor([-0.2971,  1.6819])\n",
      "\tparams: tensor([ 3.6217, -7.4209])\n",
      "Epoch: 338,Loss: 11.484293\n",
      "\tgrad: tensor([-0.2966,  1.6790])\n",
      "\tparams: tensor([ 3.6247, -7.4377])\n",
      "Epoch: 339,Loss: 11.455246\n",
      "\tgrad: tensor([-0.2961,  1.6762])\n",
      "\tparams: tensor([ 3.6276, -7.4545])\n",
      "Epoch: 340,Loss: 11.426300\n",
      "\tgrad: tensor([-0.2956,  1.6733])\n",
      "\tparams: tensor([ 3.6306, -7.4712])\n",
      "Epoch: 341,Loss: 11.397448\n",
      "\tgrad: tensor([-0.2951,  1.6705])\n",
      "\tparams: tensor([ 3.6335, -7.4879])\n",
      "Epoch: 342,Loss: 11.368696\n",
      "\tgrad: tensor([-0.2946,  1.6677])\n",
      "\tparams: tensor([ 3.6365, -7.5046])\n",
      "Epoch: 343,Loss: 11.340043\n",
      "\tgrad: tensor([-0.2941,  1.6648])\n",
      "\tparams: tensor([ 3.6394, -7.5212])\n",
      "Epoch: 344,Loss: 11.311487\n",
      "\tgrad: tensor([-0.2936,  1.6620])\n",
      "\tparams: tensor([ 3.6424, -7.5378])\n",
      "Epoch: 345,Loss: 11.283028\n",
      "\tgrad: tensor([-0.2931,  1.6592])\n",
      "\tparams: tensor([ 3.6453, -7.5544])\n",
      "Epoch: 346,Loss: 11.254662\n",
      "\tgrad: tensor([-0.2926,  1.6564])\n",
      "\tparams: tensor([ 3.6482, -7.5710])\n",
      "Epoch: 347,Loss: 11.226396\n",
      "\tgrad: tensor([-0.2921,  1.6535])\n",
      "\tparams: tensor([ 3.6511, -7.5875])\n",
      "Epoch: 348,Loss: 11.198220\n",
      "\tgrad: tensor([-0.2916,  1.6507])\n",
      "\tparams: tensor([ 3.6541, -7.6040])\n",
      "Epoch: 349,Loss: 11.170150\n",
      "\tgrad: tensor([-0.2911,  1.6479])\n",
      "\tparams: tensor([ 3.6570, -7.6205])\n",
      "Epoch: 350,Loss: 11.142170\n",
      "\tgrad: tensor([-0.2906,  1.6451])\n",
      "\tparams: tensor([ 3.6599, -7.6370])\n",
      "Epoch: 351,Loss: 11.114282\n",
      "\tgrad: tensor([-0.2901,  1.6423])\n",
      "\tparams: tensor([ 3.6628, -7.6534])\n",
      "Epoch: 352,Loss: 11.086491\n",
      "\tgrad: tensor([-0.2896,  1.6395])\n",
      "\tparams: tensor([ 3.6657, -7.6698])\n",
      "Epoch: 353,Loss: 11.058797\n",
      "\tgrad: tensor([-0.2892,  1.6368])\n",
      "\tparams: tensor([ 3.6686, -7.6861])\n",
      "Epoch: 354,Loss: 11.031193\n",
      "\tgrad: tensor([-0.2886,  1.6340])\n",
      "\tparams: tensor([ 3.6714, -7.7025])\n",
      "Epoch: 355,Loss: 11.003686\n",
      "\tgrad: tensor([-0.2882,  1.6312])\n",
      "\tparams: tensor([ 3.6743, -7.7188])\n",
      "Epoch: 356,Loss: 10.976270\n",
      "\tgrad: tensor([-0.2877,  1.6284])\n",
      "\tparams: tensor([ 3.6772, -7.7351])\n",
      "Epoch: 357,Loss: 10.948948\n",
      "\tgrad: tensor([-0.2872,  1.6257])\n",
      "\tparams: tensor([ 3.6801, -7.7513])\n",
      "Epoch: 358,Loss: 10.921719\n",
      "\tgrad: tensor([-0.2867,  1.6229])\n",
      "\tparams: tensor([ 3.6829, -7.7676])\n",
      "Epoch: 359,Loss: 10.894581\n",
      "\tgrad: tensor([-0.2862,  1.6201])\n",
      "\tparams: tensor([ 3.6858, -7.7838])\n",
      "Epoch: 360,Loss: 10.867537\n",
      "\tgrad: tensor([-0.2857,  1.6174])\n",
      "\tparams: tensor([ 3.6887, -7.7999])\n",
      "Epoch: 361,Loss: 10.840583\n",
      "\tgrad: tensor([-0.2852,  1.6146])\n",
      "\tparams: tensor([ 3.6915, -7.8161])\n",
      "Epoch: 362,Loss: 10.813721\n",
      "\tgrad: tensor([-0.2847,  1.6119])\n",
      "\tparams: tensor([ 3.6944, -7.8322])\n",
      "Epoch: 363,Loss: 10.786950\n",
      "\tgrad: tensor([-0.2843,  1.6092])\n",
      "\tparams: tensor([ 3.6972, -7.8483])\n",
      "Epoch: 364,Loss: 10.760270\n",
      "\tgrad: tensor([-0.2838,  1.6064])\n",
      "\tparams: tensor([ 3.7000, -7.8644])\n",
      "Epoch: 365,Loss: 10.733681\n",
      "\tgrad: tensor([-0.2833,  1.6037])\n",
      "\tparams: tensor([ 3.7029, -7.8804])\n",
      "Epoch: 366,Loss: 10.707184\n",
      "\tgrad: tensor([-0.2828,  1.6010])\n",
      "\tparams: tensor([ 3.7057, -7.8964])\n",
      "Epoch: 367,Loss: 10.680775\n",
      "\tgrad: tensor([-0.2823,  1.5983])\n",
      "\tparams: tensor([ 3.7085, -7.9124])\n",
      "Epoch: 368,Loss: 10.654454\n",
      "\tgrad: tensor([-0.2819,  1.5955])\n",
      "\tparams: tensor([ 3.7113, -7.9284])\n",
      "Epoch: 369,Loss: 10.628225\n",
      "\tgrad: tensor([-0.2814,  1.5928])\n",
      "\tparams: tensor([ 3.7142, -7.9443])\n",
      "Epoch: 370,Loss: 10.602086\n",
      "\tgrad: tensor([-0.2809,  1.5901])\n",
      "\tparams: tensor([ 3.7170, -7.9602])\n",
      "Epoch: 371,Loss: 10.576034\n",
      "\tgrad: tensor([-0.2804,  1.5874])\n",
      "\tparams: tensor([ 3.7198, -7.9761])\n",
      "Epoch: 372,Loss: 10.550071\n",
      "\tgrad: tensor([-0.2799,  1.5847])\n",
      "\tparams: tensor([ 3.7226, -7.9919])\n",
      "Epoch: 373,Loss: 10.524194\n",
      "\tgrad: tensor([-0.2795,  1.5820])\n",
      "\tparams: tensor([ 3.7254, -8.0077])\n",
      "Epoch: 374,Loss: 10.498409\n",
      "\tgrad: tensor([-0.2790,  1.5794])\n",
      "\tparams: tensor([ 3.7282, -8.0235])\n",
      "Epoch: 375,Loss: 10.472707\n",
      "\tgrad: tensor([-0.2785,  1.5767])\n",
      "\tparams: tensor([ 3.7309, -8.0393])\n",
      "Epoch: 376,Loss: 10.447093\n",
      "\tgrad: tensor([-0.2780,  1.5740])\n",
      "\tparams: tensor([ 3.7337, -8.0550])\n",
      "Epoch: 377,Loss: 10.421569\n",
      "\tgrad: tensor([-0.2776,  1.5713])\n",
      "\tparams: tensor([ 3.7365, -8.0707])\n",
      "Epoch: 378,Loss: 10.396132\n",
      "\tgrad: tensor([-0.2771,  1.5686])\n",
      "\tparams: tensor([ 3.7393, -8.0864])\n",
      "Epoch: 379,Loss: 10.370779\n",
      "\tgrad: tensor([-0.2766,  1.5660])\n",
      "\tparams: tensor([ 3.7420, -8.1021])\n",
      "Epoch: 380,Loss: 10.345510\n",
      "\tgrad: tensor([-0.2762,  1.5633])\n",
      "\tparams: tensor([ 3.7448, -8.1177])\n",
      "Epoch: 381,Loss: 10.320328\n",
      "\tgrad: tensor([-0.2757,  1.5607])\n",
      "\tparams: tensor([ 3.7476, -8.1333])\n",
      "Epoch: 382,Loss: 10.295234\n",
      "\tgrad: tensor([-0.2752,  1.5580])\n",
      "\tparams: tensor([ 3.7503, -8.1489])\n",
      "Epoch: 383,Loss: 10.270224\n",
      "\tgrad: tensor([-0.2748,  1.5554])\n",
      "\tparams: tensor([ 3.7531, -8.1645])\n",
      "Epoch: 384,Loss: 10.245296\n",
      "\tgrad: tensor([-0.2743,  1.5527])\n",
      "\tparams: tensor([ 3.7558, -8.1800])\n",
      "Epoch: 385,Loss: 10.220457\n",
      "\tgrad: tensor([-0.2738,  1.5501])\n",
      "\tparams: tensor([ 3.7585, -8.1955])\n",
      "Epoch: 386,Loss: 10.195701\n",
      "\tgrad: tensor([-0.2734,  1.5475])\n",
      "\tparams: tensor([ 3.7613, -8.2110])\n",
      "Epoch: 387,Loss: 10.171029\n",
      "\tgrad: tensor([-0.2729,  1.5448])\n",
      "\tparams: tensor([ 3.7640, -8.2264])\n",
      "Epoch: 388,Loss: 10.146438\n",
      "\tgrad: tensor([-0.2724,  1.5422])\n",
      "\tparams: tensor([ 3.7667, -8.2418])\n",
      "Epoch: 389,Loss: 10.121935\n",
      "\tgrad: tensor([-0.2720,  1.5396])\n",
      "\tparams: tensor([ 3.7694, -8.2572])\n",
      "Epoch: 390,Loss: 10.097512\n",
      "\tgrad: tensor([-0.2715,  1.5370])\n",
      "\tparams: tensor([ 3.7722, -8.2726])\n",
      "Epoch: 391,Loss: 10.073173\n",
      "\tgrad: tensor([-0.2711,  1.5344])\n",
      "\tparams: tensor([ 3.7749, -8.2879])\n",
      "Epoch: 392,Loss: 10.048919\n",
      "\tgrad: tensor([-0.2706,  1.5317])\n",
      "\tparams: tensor([ 3.7776, -8.3033])\n",
      "Epoch: 393,Loss: 10.024743\n",
      "\tgrad: tensor([-0.2701,  1.5291])\n",
      "\tparams: tensor([ 3.7803, -8.3185])\n",
      "Epoch: 394,Loss: 10.000652\n",
      "\tgrad: tensor([-0.2697,  1.5265])\n",
      "\tparams: tensor([ 3.7830, -8.3338])\n",
      "Epoch: 395,Loss: 9.976640\n",
      "\tgrad: tensor([-0.2692,  1.5240])\n",
      "\tparams: tensor([ 3.7857, -8.3491])\n",
      "Epoch: 396,Loss: 9.952712\n",
      "\tgrad: tensor([-0.2688,  1.5214])\n",
      "\tparams: tensor([ 3.7884, -8.3643])\n",
      "Epoch: 397,Loss: 9.928862\n",
      "\tgrad: tensor([-0.2683,  1.5188])\n",
      "\tparams: tensor([ 3.7910, -8.3795])\n",
      "Epoch: 398,Loss: 9.905093\n",
      "\tgrad: tensor([-0.2678,  1.5162])\n",
      "\tparams: tensor([ 3.7937, -8.3946])\n",
      "Epoch: 399,Loss: 9.881409\n",
      "\tgrad: tensor([-0.2674,  1.5136])\n",
      "\tparams: tensor([ 3.7964, -8.4098])\n",
      "Epoch: 400,Loss: 9.857804\n",
      "\tgrad: tensor([-0.2669,  1.5111])\n",
      "\tparams: tensor([ 3.7991, -8.4249])\n",
      "Epoch: 401,Loss: 9.834277\n",
      "\tgrad: tensor([-0.2665,  1.5085])\n",
      "\tparams: tensor([ 3.8017, -8.4399])\n",
      "Epoch: 402,Loss: 9.810831\n",
      "\tgrad: tensor([-0.2660,  1.5059])\n",
      "\tparams: tensor([ 3.8044, -8.4550])\n",
      "Epoch: 403,Loss: 9.787466\n",
      "\tgrad: tensor([-0.2656,  1.5034])\n",
      "\tparams: tensor([ 3.8070, -8.4700])\n",
      "Epoch: 404,Loss: 9.764176\n",
      "\tgrad: tensor([-0.2651,  1.5008])\n",
      "\tparams: tensor([ 3.8097, -8.4851])\n",
      "Epoch: 405,Loss: 9.740973\n",
      "\tgrad: tensor([-0.2647,  1.4983])\n",
      "\tparams: tensor([ 3.8123, -8.5000])\n",
      "Epoch: 406,Loss: 9.717843\n",
      "\tgrad: tensor([-0.2642,  1.4957])\n",
      "\tparams: tensor([ 3.8150, -8.5150])\n",
      "Epoch: 407,Loss: 9.694793\n",
      "\tgrad: tensor([-0.2638,  1.4932])\n",
      "\tparams: tensor([ 3.8176, -8.5299])\n",
      "Epoch: 408,Loss: 9.671824\n",
      "\tgrad: tensor([-0.2633,  1.4906])\n",
      "\tparams: tensor([ 3.8202, -8.5448])\n",
      "Epoch: 409,Loss: 9.648926\n",
      "\tgrad: tensor([-0.2629,  1.4881])\n",
      "\tparams: tensor([ 3.8229, -8.5597])\n",
      "Epoch: 410,Loss: 9.626110\n",
      "\tgrad: tensor([-0.2624,  1.4856])\n",
      "\tparams: tensor([ 3.8255, -8.5746])\n",
      "Epoch: 411,Loss: 9.603373\n",
      "\tgrad: tensor([-0.2620,  1.4831])\n",
      "\tparams: tensor([ 3.8281, -8.5894])\n",
      "Epoch: 412,Loss: 9.580709\n",
      "\tgrad: tensor([-0.2615,  1.4805])\n",
      "\tparams: tensor([ 3.8307, -8.6042])\n",
      "Epoch: 413,Loss: 9.558125\n",
      "\tgrad: tensor([-0.2611,  1.4780])\n",
      "\tparams: tensor([ 3.8333, -8.6190])\n",
      "Epoch: 414,Loss: 9.535617\n",
      "\tgrad: tensor([-0.2606,  1.4755])\n",
      "\tparams: tensor([ 3.8360, -8.6337])\n",
      "Epoch: 415,Loss: 9.513184\n",
      "\tgrad: tensor([-0.2602,  1.4730])\n",
      "\tparams: tensor([ 3.8386, -8.6485])\n",
      "Epoch: 416,Loss: 9.490829\n",
      "\tgrad: tensor([-0.2598,  1.4705])\n",
      "\tparams: tensor([ 3.8412, -8.6632])\n",
      "Epoch: 417,Loss: 9.468551\n",
      "\tgrad: tensor([-0.2593,  1.4680])\n",
      "\tparams: tensor([ 3.8437, -8.6779])\n",
      "Epoch: 418,Loss: 9.446347\n",
      "\tgrad: tensor([-0.2589,  1.4655])\n",
      "\tparams: tensor([ 3.8463, -8.6925])\n",
      "Epoch: 419,Loss: 9.424216\n",
      "\tgrad: tensor([-0.2584,  1.4630])\n",
      "\tparams: tensor([ 3.8489, -8.7071])\n",
      "Epoch: 420,Loss: 9.402164\n",
      "\tgrad: tensor([-0.2580,  1.4605])\n",
      "\tparams: tensor([ 3.8515, -8.7217])\n",
      "Epoch: 421,Loss: 9.380184\n",
      "\tgrad: tensor([-0.2576,  1.4581])\n",
      "\tparams: tensor([ 3.8541, -8.7363])\n",
      "Epoch: 422,Loss: 9.358282\n",
      "\tgrad: tensor([-0.2571,  1.4556])\n",
      "\tparams: tensor([ 3.8566, -8.7509])\n",
      "Epoch: 423,Loss: 9.336448\n",
      "\tgrad: tensor([-0.2567,  1.4531])\n",
      "\tparams: tensor([ 3.8592, -8.7654])\n",
      "Epoch: 424,Loss: 9.314695\n",
      "\tgrad: tensor([-0.2563,  1.4506])\n",
      "\tparams: tensor([ 3.8618, -8.7799])\n",
      "Epoch: 425,Loss: 9.293012\n",
      "\tgrad: tensor([-0.2558,  1.4482])\n",
      "\tparams: tensor([ 3.8643, -8.7944])\n",
      "Epoch: 426,Loss: 9.271403\n",
      "\tgrad: tensor([-0.2554,  1.4457])\n",
      "\tparams: tensor([ 3.8669, -8.8089])\n",
      "Epoch: 427,Loss: 9.249871\n",
      "\tgrad: tensor([-0.2550,  1.4433])\n",
      "\tparams: tensor([ 3.8694, -8.8233])\n",
      "Epoch: 428,Loss: 9.228410\n",
      "\tgrad: tensor([-0.2545,  1.4408])\n",
      "\tparams: tensor([ 3.8720, -8.8377])\n",
      "Epoch: 429,Loss: 9.207022\n",
      "\tgrad: tensor([-0.2541,  1.4384])\n",
      "\tparams: tensor([ 3.8745, -8.8521])\n",
      "Epoch: 430,Loss: 9.185704\n",
      "\tgrad: tensor([-0.2537,  1.4359])\n",
      "\tparams: tensor([ 3.8771, -8.8664])\n",
      "Epoch: 431,Loss: 9.164462\n",
      "\tgrad: tensor([-0.2532,  1.4335])\n",
      "\tparams: tensor([ 3.8796, -8.8808])\n",
      "Epoch: 432,Loss: 9.143289\n",
      "\tgrad: tensor([-0.2528,  1.4310])\n",
      "\tparams: tensor([ 3.8821, -8.8951])\n",
      "Epoch: 433,Loss: 9.122189\n",
      "\tgrad: tensor([-0.2524,  1.4286])\n",
      "\tparams: tensor([ 3.8846, -8.9094])\n",
      "Epoch: 434,Loss: 9.101160\n",
      "\tgrad: tensor([-0.2519,  1.4262])\n",
      "\tparams: tensor([ 3.8872, -8.9236])\n",
      "Epoch: 435,Loss: 9.080204\n",
      "\tgrad: tensor([-0.2515,  1.4238])\n",
      "\tparams: tensor([ 3.8897, -8.9379])\n",
      "Epoch: 436,Loss: 9.059318\n",
      "\tgrad: tensor([-0.2511,  1.4213])\n",
      "\tparams: tensor([ 3.8922, -8.9521])\n",
      "Epoch: 437,Loss: 9.038502\n",
      "\tgrad: tensor([-0.2507,  1.4189])\n",
      "\tparams: tensor([ 3.8947, -8.9663])\n",
      "Epoch: 438,Loss: 9.017757\n",
      "\tgrad: tensor([-0.2502,  1.4165])\n",
      "\tparams: tensor([ 3.8972, -8.9804])\n",
      "Epoch: 439,Loss: 8.997084\n",
      "\tgrad: tensor([-0.2498,  1.4141])\n",
      "\tparams: tensor([ 3.8997, -8.9946])\n",
      "Epoch: 440,Loss: 8.976479\n",
      "\tgrad: tensor([-0.2494,  1.4117])\n",
      "\tparams: tensor([ 3.9022, -9.0087])\n",
      "Epoch: 441,Loss: 8.955944\n",
      "\tgrad: tensor([-0.2489,  1.4093])\n",
      "\tparams: tensor([ 3.9047, -9.0228])\n",
      "Epoch: 442,Loss: 8.935480\n",
      "\tgrad: tensor([-0.2485,  1.4069])\n",
      "\tparams: tensor([ 3.9072, -9.0369])\n",
      "Epoch: 443,Loss: 8.915089\n",
      "\tgrad: tensor([-0.2481,  1.4045])\n",
      "\tparams: tensor([ 3.9096, -9.0509])\n",
      "Epoch: 444,Loss: 8.894762\n",
      "\tgrad: tensor([-0.2477,  1.4021])\n",
      "\tparams: tensor([ 3.9121, -9.0649])\n",
      "Epoch: 445,Loss: 8.874508\n",
      "\tgrad: tensor([-0.2473,  1.3998])\n",
      "\tparams: tensor([ 3.9146, -9.0789])\n",
      "Epoch: 446,Loss: 8.854318\n",
      "\tgrad: tensor([-0.2468,  1.3974])\n",
      "\tparams: tensor([ 3.9171, -9.0929])\n",
      "Epoch: 447,Loss: 8.834197\n",
      "\tgrad: tensor([-0.2464,  1.3950])\n",
      "\tparams: tensor([ 3.9195, -9.1068])\n",
      "Epoch: 448,Loss: 8.814149\n",
      "\tgrad: tensor([-0.2460,  1.3926])\n",
      "\tparams: tensor([ 3.9220, -9.1208])\n",
      "Epoch: 449,Loss: 8.794162\n",
      "\tgrad: tensor([-0.2456,  1.3903])\n",
      "\tparams: tensor([ 3.9244, -9.1347])\n",
      "Epoch: 450,Loss: 8.774253\n",
      "\tgrad: tensor([-0.2452,  1.3879])\n",
      "\tparams: tensor([ 3.9269, -9.1486])\n",
      "Epoch: 451,Loss: 8.754405\n",
      "\tgrad: tensor([-0.2448,  1.3856])\n",
      "\tparams: tensor([ 3.9293, -9.1624])\n",
      "Epoch: 452,Loss: 8.734623\n",
      "\tgrad: tensor([-0.2443,  1.3832])\n",
      "\tparams: tensor([ 3.9318, -9.1762])\n",
      "Epoch: 453,Loss: 8.714911\n",
      "\tgrad: tensor([-0.2439,  1.3808])\n",
      "\tparams: tensor([ 3.9342, -9.1901])\n",
      "Epoch: 454,Loss: 8.695266\n",
      "\tgrad: tensor([-0.2435,  1.3785])\n",
      "\tparams: tensor([ 3.9367, -9.2038])\n",
      "Epoch: 455,Loss: 8.675688\n",
      "\tgrad: tensor([-0.2431,  1.3762])\n",
      "\tparams: tensor([ 3.9391, -9.2176])\n",
      "Epoch: 456,Loss: 8.656173\n",
      "\tgrad: tensor([-0.2427,  1.3738])\n",
      "\tparams: tensor([ 3.9415, -9.2313])\n",
      "Epoch: 457,Loss: 8.636729\n",
      "\tgrad: tensor([-0.2423,  1.3715])\n",
      "\tparams: tensor([ 3.9439, -9.2451])\n",
      "Epoch: 458,Loss: 8.617347\n",
      "\tgrad: tensor([-0.2419,  1.3692])\n",
      "\tparams: tensor([ 3.9464, -9.2587])\n",
      "Epoch: 459,Loss: 8.598029\n",
      "\tgrad: tensor([-0.2414,  1.3668])\n",
      "\tparams: tensor([ 3.9488, -9.2724])\n",
      "Epoch: 460,Loss: 8.578781\n",
      "\tgrad: tensor([-0.2410,  1.3645])\n",
      "\tparams: tensor([ 3.9512, -9.2861])\n",
      "Epoch: 461,Loss: 8.559597\n",
      "\tgrad: tensor([-0.2406,  1.3622])\n",
      "\tparams: tensor([ 3.9536, -9.2997])\n",
      "Epoch: 462,Loss: 8.540479\n",
      "\tgrad: tensor([-0.2402,  1.3599])\n",
      "\tparams: tensor([ 3.9560, -9.3133])\n",
      "Epoch: 463,Loss: 8.521426\n",
      "\tgrad: tensor([-0.2398,  1.3576])\n",
      "\tparams: tensor([ 3.9584, -9.3269])\n",
      "Epoch: 464,Loss: 8.502437\n",
      "\tgrad: tensor([-0.2394,  1.3553])\n",
      "\tparams: tensor([ 3.9608, -9.3404])\n",
      "Epoch: 465,Loss: 8.483517\n",
      "\tgrad: tensor([-0.2390,  1.3530])\n",
      "\tparams: tensor([ 3.9632, -9.3539])\n",
      "Epoch: 466,Loss: 8.464652\n",
      "\tgrad: tensor([-0.2386,  1.3507])\n",
      "\tparams: tensor([ 3.9656, -9.3674])\n",
      "Epoch: 467,Loss: 8.445858\n",
      "\tgrad: tensor([-0.2382,  1.3484])\n",
      "\tparams: tensor([ 3.9679, -9.3809])\n",
      "Epoch: 468,Loss: 8.427128\n",
      "\tgrad: tensor([-0.2378,  1.3461])\n",
      "\tparams: tensor([ 3.9703, -9.3944])\n",
      "Epoch: 469,Loss: 8.408454\n",
      "\tgrad: tensor([-0.2374,  1.3438])\n",
      "\tparams: tensor([ 3.9727, -9.4078])\n",
      "Epoch: 470,Loss: 8.389848\n",
      "\tgrad: tensor([-0.2370,  1.3415])\n",
      "\tparams: tensor([ 3.9751, -9.4212])\n",
      "Epoch: 471,Loss: 8.371305\n",
      "\tgrad: tensor([-0.2366,  1.3392])\n",
      "\tparams: tensor([ 3.9774, -9.4346])\n",
      "Epoch: 472,Loss: 8.352828\n",
      "\tgrad: tensor([-0.2362,  1.3370])\n",
      "\tparams: tensor([ 3.9798, -9.4480])\n",
      "Epoch: 473,Loss: 8.334409\n",
      "\tgrad: tensor([-0.2358,  1.3347])\n",
      "\tparams: tensor([ 3.9822, -9.4614])\n",
      "Epoch: 474,Loss: 8.316054\n",
      "\tgrad: tensor([-0.2354,  1.3324])\n",
      "\tparams: tensor([ 3.9845, -9.4747])\n",
      "Epoch: 475,Loss: 8.297764\n",
      "\tgrad: tensor([-0.2350,  1.3301])\n",
      "\tparams: tensor([ 3.9869, -9.4880])\n",
      "Epoch: 476,Loss: 8.279534\n",
      "\tgrad: tensor([-0.2346,  1.3279])\n",
      "\tparams: tensor([ 3.9892, -9.5013])\n",
      "Epoch: 477,Loss: 8.261369\n",
      "\tgrad: tensor([-0.2342,  1.3256])\n",
      "\tparams: tensor([ 3.9915, -9.5145])\n",
      "Epoch: 478,Loss: 8.243259\n",
      "\tgrad: tensor([-0.2338,  1.3234])\n",
      "\tparams: tensor([ 3.9939, -9.5277])\n",
      "Epoch: 479,Loss: 8.225213\n",
      "\tgrad: tensor([-0.2334,  1.3211])\n",
      "\tparams: tensor([ 3.9962, -9.5410])\n",
      "Epoch: 480,Loss: 8.207231\n",
      "\tgrad: tensor([-0.2330,  1.3189])\n",
      "\tparams: tensor([ 3.9985, -9.5541])\n",
      "Epoch: 481,Loss: 8.189310\n",
      "\tgrad: tensor([-0.2326,  1.3166])\n",
      "\tparams: tensor([ 4.0009, -9.5673])\n",
      "Epoch: 482,Loss: 8.171452\n",
      "\tgrad: tensor([-0.2322,  1.3144])\n",
      "\tparams: tensor([ 4.0032, -9.5805])\n",
      "Epoch: 483,Loss: 8.153647\n",
      "\tgrad: tensor([-0.2318,  1.3122])\n",
      "\tparams: tensor([ 4.0055, -9.5936])\n",
      "Epoch: 484,Loss: 8.135906\n",
      "\tgrad: tensor([-0.2314,  1.3100])\n",
      "\tparams: tensor([ 4.0078, -9.6067])\n",
      "Epoch: 485,Loss: 8.118226\n",
      "\tgrad: tensor([-0.2310,  1.3077])\n",
      "\tparams: tensor([ 4.0101, -9.6198])\n",
      "Epoch: 486,Loss: 8.100607\n",
      "\tgrad: tensor([-0.2306,  1.3055])\n",
      "\tparams: tensor([ 4.0124, -9.6328])\n",
      "Epoch: 487,Loss: 8.083045\n",
      "\tgrad: tensor([-0.2302,  1.3033])\n",
      "\tparams: tensor([ 4.0147, -9.6458])\n",
      "Epoch: 488,Loss: 8.065548\n",
      "\tgrad: tensor([-0.2298,  1.3011])\n",
      "\tparams: tensor([ 4.0170, -9.6589])\n",
      "Epoch: 489,Loss: 8.048104\n",
      "\tgrad: tensor([-0.2295,  1.2989])\n",
      "\tparams: tensor([ 4.0193, -9.6718])\n",
      "Epoch: 490,Loss: 8.030724\n",
      "\tgrad: tensor([-0.2291,  1.2967])\n",
      "\tparams: tensor([ 4.0216, -9.6848])\n",
      "Epoch: 491,Loss: 8.013401\n",
      "\tgrad: tensor([-0.2287,  1.2945])\n",
      "\tparams: tensor([ 4.0239, -9.6978])\n",
      "Epoch: 492,Loss: 7.996137\n",
      "\tgrad: tensor([-0.2283,  1.2923])\n",
      "\tparams: tensor([ 4.0262, -9.7107])\n",
      "Epoch: 493,Loss: 7.978930\n",
      "\tgrad: tensor([-0.2279,  1.2901])\n",
      "\tparams: tensor([ 4.0285, -9.7236])\n",
      "Epoch: 494,Loss: 7.961783\n",
      "\tgrad: tensor([-0.2275,  1.2879])\n",
      "\tparams: tensor([ 4.0308, -9.7365])\n",
      "Epoch: 495,Loss: 7.944690\n",
      "\tgrad: tensor([-0.2271,  1.2857])\n",
      "\tparams: tensor([ 4.0330, -9.7493])\n",
      "Epoch: 496,Loss: 7.927663\n",
      "\tgrad: tensor([-0.2267,  1.2835])\n",
      "\tparams: tensor([ 4.0353, -9.7621])\n",
      "Epoch: 497,Loss: 7.910690\n",
      "\tgrad: tensor([-0.2263,  1.2813])\n",
      "\tparams: tensor([ 4.0376, -9.7750])\n",
      "Epoch: 498,Loss: 7.893775\n",
      "\tgrad: tensor([-0.2260,  1.2791])\n",
      "\tparams: tensor([ 4.0398, -9.7878])\n",
      "Epoch: 499,Loss: 7.876915\n",
      "\tgrad: tensor([-0.2256,  1.2770])\n",
      "\tparams: tensor([ 4.0421, -9.8005])\n",
      "Epoch: 500,Loss: 7.860115\n",
      "\tgrad: tensor([-0.2252,  1.2748])\n",
      "\tparams: tensor([ 4.0443, -9.8133])\n",
      "Epoch: 501,Loss: 7.843369\n",
      "\tgrad: tensor([-0.2248,  1.2726])\n",
      "\tparams: tensor([ 4.0466, -9.8260])\n",
      "Epoch: 502,Loss: 7.826683\n",
      "\tgrad: tensor([-0.2244,  1.2705])\n",
      "\tparams: tensor([ 4.0488, -9.8387])\n",
      "Epoch: 503,Loss: 7.810053\n",
      "\tgrad: tensor([-0.2241,  1.2683])\n",
      "\tparams: tensor([ 4.0511, -9.8514])\n",
      "Epoch: 504,Loss: 7.793481\n",
      "\tgrad: tensor([-0.2237,  1.2662])\n",
      "\tparams: tensor([ 4.0533, -9.8640])\n",
      "Epoch: 505,Loss: 7.776962\n",
      "\tgrad: tensor([-0.2233,  1.2640])\n",
      "\tparams: tensor([ 4.0555, -9.8767])\n",
      "Epoch: 506,Loss: 7.760498\n",
      "\tgrad: tensor([-0.2229,  1.2619])\n",
      "\tparams: tensor([ 4.0578, -9.8893])\n",
      "Epoch: 507,Loss: 7.744092\n",
      "\tgrad: tensor([-0.2225,  1.2597])\n",
      "\tparams: tensor([ 4.0600, -9.9019])\n",
      "Epoch: 508,Loss: 7.727745\n",
      "\tgrad: tensor([-0.2222,  1.2576])\n",
      "\tparams: tensor([ 4.0622, -9.9145])\n",
      "Epoch: 509,Loss: 7.711449\n",
      "\tgrad: tensor([-0.2218,  1.2554])\n",
      "\tparams: tensor([ 4.0644, -9.9270])\n",
      "Epoch: 510,Loss: 7.695211\n",
      "\tgrad: tensor([-0.2214,  1.2533])\n",
      "\tparams: tensor([ 4.0666, -9.9396])\n",
      "Epoch: 511,Loss: 7.679024\n",
      "\tgrad: tensor([-0.2210,  1.2512])\n",
      "\tparams: tensor([ 4.0688, -9.9521])\n",
      "Epoch: 512,Loss: 7.662896\n",
      "\tgrad: tensor([-0.2207,  1.2490])\n",
      "\tparams: tensor([ 4.0710, -9.9646])\n",
      "Epoch: 513,Loss: 7.646820\n",
      "\tgrad: tensor([-0.2203,  1.2469])\n",
      "\tparams: tensor([ 4.0733, -9.9770])\n",
      "Epoch: 514,Loss: 7.630803\n",
      "\tgrad: tensor([-0.2199,  1.2448])\n",
      "\tparams: tensor([ 4.0754, -9.9895])\n",
      "Epoch: 515,Loss: 7.614836\n",
      "\tgrad: tensor([-0.2195,  1.2427])\n",
      "\tparams: tensor([  4.0776, -10.0019])\n",
      "Epoch: 516,Loss: 7.598925\n",
      "\tgrad: tensor([-0.2192,  1.2406])\n",
      "\tparams: tensor([  4.0798, -10.0143])\n",
      "Epoch: 517,Loss: 7.583069\n",
      "\tgrad: tensor([-0.2188,  1.2385])\n",
      "\tparams: tensor([  4.0820, -10.0267])\n",
      "Epoch: 518,Loss: 7.567265\n",
      "\tgrad: tensor([-0.2184,  1.2364])\n",
      "\tparams: tensor([  4.0842, -10.0391])\n",
      "Epoch: 519,Loss: 7.551515\n",
      "\tgrad: tensor([-0.2180,  1.2343])\n",
      "\tparams: tensor([  4.0864, -10.0514])\n",
      "Epoch: 520,Loss: 7.535818\n",
      "\tgrad: tensor([-0.2177,  1.2322])\n",
      "\tparams: tensor([  4.0886, -10.0637])\n",
      "Epoch: 521,Loss: 7.520176\n",
      "\tgrad: tensor([-0.2173,  1.2301])\n",
      "\tparams: tensor([  4.0907, -10.0760])\n",
      "Epoch: 522,Loss: 7.504587\n",
      "\tgrad: tensor([-0.2169,  1.2280])\n",
      "\tparams: tensor([  4.0929, -10.0883])\n",
      "Epoch: 523,Loss: 7.489048\n",
      "\tgrad: tensor([-0.2165,  1.2259])\n",
      "\tparams: tensor([  4.0951, -10.1006])\n",
      "Epoch: 524,Loss: 7.473566\n",
      "\tgrad: tensor([-0.2162,  1.2238])\n",
      "\tparams: tensor([  4.0972, -10.1128])\n",
      "Epoch: 525,Loss: 7.458135\n",
      "\tgrad: tensor([-0.2158,  1.2217])\n",
      "\tparams: tensor([  4.0994, -10.1250])\n",
      "Epoch: 526,Loss: 7.442750\n",
      "\tgrad: tensor([-0.2155,  1.2197])\n",
      "\tparams: tensor([  4.1015, -10.1372])\n",
      "Epoch: 527,Loss: 7.427427\n",
      "\tgrad: tensor([-0.2151,  1.2176])\n",
      "\tparams: tensor([  4.1037, -10.1494])\n",
      "Epoch: 528,Loss: 7.412152\n",
      "\tgrad: tensor([-0.2147,  1.2155])\n",
      "\tparams: tensor([  4.1058, -10.1616])\n",
      "Epoch: 529,Loss: 7.396928\n",
      "\tgrad: tensor([-0.2144,  1.2135])\n",
      "\tparams: tensor([  4.1080, -10.1737])\n",
      "Epoch: 530,Loss: 7.381757\n",
      "\tgrad: tensor([-0.2140,  1.2114])\n",
      "\tparams: tensor([  4.1101, -10.1858])\n",
      "Epoch: 531,Loss: 7.366637\n",
      "\tgrad: tensor([-0.2136,  1.2093])\n",
      "\tparams: tensor([  4.1123, -10.1979])\n",
      "Epoch: 532,Loss: 7.351567\n",
      "\tgrad: tensor([-0.2133,  1.2073])\n",
      "\tparams: tensor([  4.1144, -10.2100])\n",
      "Epoch: 533,Loss: 7.336549\n",
      "\tgrad: tensor([-0.2129,  1.2052])\n",
      "\tparams: tensor([  4.1165, -10.2220])\n",
      "Epoch: 534,Loss: 7.321584\n",
      "\tgrad: tensor([-0.2125,  1.2032])\n",
      "\tparams: tensor([  4.1187, -10.2340])\n",
      "Epoch: 535,Loss: 7.306671\n",
      "\tgrad: tensor([-0.2122,  1.2012])\n",
      "\tparams: tensor([  4.1208, -10.2461])\n",
      "Epoch: 536,Loss: 7.291804\n",
      "\tgrad: tensor([-0.2118,  1.1991])\n",
      "\tparams: tensor([  4.1229, -10.2581])\n",
      "Epoch: 537,Loss: 7.276989\n",
      "\tgrad: tensor([-0.2115,  1.1971])\n",
      "\tparams: tensor([  4.1250, -10.2700])\n",
      "Epoch: 538,Loss: 7.262227\n",
      "\tgrad: tensor([-0.2111,  1.1950])\n",
      "\tparams: tensor([  4.1271, -10.2820])\n",
      "Epoch: 539,Loss: 7.247512\n",
      "\tgrad: tensor([-0.2108,  1.1930])\n",
      "\tparams: tensor([  4.1292, -10.2939])\n",
      "Epoch: 540,Loss: 7.232845\n",
      "\tgrad: tensor([-0.2104,  1.1910])\n",
      "\tparams: tensor([  4.1313, -10.3058])\n",
      "Epoch: 541,Loss: 7.218231\n",
      "\tgrad: tensor([-0.2100,  1.1890])\n",
      "\tparams: tensor([  4.1334, -10.3177])\n",
      "Epoch: 542,Loss: 7.203665\n",
      "\tgrad: tensor([-0.2097,  1.1869])\n",
      "\tparams: tensor([  4.1355, -10.3296])\n",
      "Epoch: 543,Loss: 7.189151\n",
      "\tgrad: tensor([-0.2093,  1.1849])\n",
      "\tparams: tensor([  4.1376, -10.3414])\n",
      "Epoch: 544,Loss: 7.174683\n",
      "\tgrad: tensor([-0.2090,  1.1829])\n",
      "\tparams: tensor([  4.1397, -10.3533])\n",
      "Epoch: 545,Loss: 7.160266\n",
      "\tgrad: tensor([-0.2086,  1.1809])\n",
      "\tparams: tensor([  4.1418, -10.3651])\n",
      "Epoch: 546,Loss: 7.145897\n",
      "\tgrad: tensor([-0.2083,  1.1789])\n",
      "\tparams: tensor([  4.1439, -10.3769])\n",
      "Epoch: 547,Loss: 7.131581\n",
      "\tgrad: tensor([-0.2079,  1.1769])\n",
      "\tparams: tensor([  4.1460, -10.3886])\n",
      "Epoch: 548,Loss: 7.117305\n",
      "\tgrad: tensor([-0.2075,  1.1749])\n",
      "\tparams: tensor([  4.1480, -10.4004])\n",
      "Epoch: 549,Loss: 7.103083\n",
      "\tgrad: tensor([-0.2072,  1.1729])\n",
      "\tparams: tensor([  4.1501, -10.4121])\n",
      "Epoch: 550,Loss: 7.088911\n",
      "\tgrad: tensor([-0.2068,  1.1709])\n",
      "\tparams: tensor([  4.1522, -10.4238])\n",
      "Epoch: 551,Loss: 7.074785\n",
      "\tgrad: tensor([-0.2065,  1.1689])\n",
      "\tparams: tensor([  4.1542, -10.4355])\n",
      "Epoch: 552,Loss: 7.060707\n",
      "\tgrad: tensor([-0.2062,  1.1669])\n",
      "\tparams: tensor([  4.1563, -10.4472])\n",
      "Epoch: 553,Loss: 7.046676\n",
      "\tgrad: tensor([-0.2058,  1.1649])\n",
      "\tparams: tensor([  4.1584, -10.4588])\n",
      "Epoch: 554,Loss: 7.032695\n",
      "\tgrad: tensor([-0.2054,  1.1630])\n",
      "\tparams: tensor([  4.1604, -10.4704])\n",
      "Epoch: 555,Loss: 7.018755\n",
      "\tgrad: tensor([-0.2051,  1.1610])\n",
      "\tparams: tensor([  4.1625, -10.4821])\n",
      "Epoch: 556,Loss: 7.004870\n",
      "\tgrad: tensor([-0.2047,  1.1590])\n",
      "\tparams: tensor([  4.1645, -10.4936])\n",
      "Epoch: 557,Loss: 6.991028\n",
      "\tgrad: tensor([-0.2044,  1.1571])\n",
      "\tparams: tensor([  4.1666, -10.5052])\n",
      "Epoch: 558,Loss: 6.977232\n",
      "\tgrad: tensor([-0.2041,  1.1551])\n",
      "\tparams: tensor([  4.1686, -10.5168])\n",
      "Epoch: 559,Loss: 6.963488\n",
      "\tgrad: tensor([-0.2037,  1.1531])\n",
      "\tparams: tensor([  4.1706, -10.5283])\n",
      "Epoch: 560,Loss: 6.949787\n",
      "\tgrad: tensor([-0.2034,  1.1512])\n",
      "\tparams: tensor([  4.1727, -10.5398])\n",
      "Epoch: 561,Loss: 6.936135\n",
      "\tgrad: tensor([-0.2030,  1.1492])\n",
      "\tparams: tensor([  4.1747, -10.5513])\n",
      "Epoch: 562,Loss: 6.922528\n",
      "\tgrad: tensor([-0.2027,  1.1473])\n",
      "\tparams: tensor([  4.1767, -10.5628])\n",
      "Epoch: 563,Loss: 6.908967\n",
      "\tgrad: tensor([-0.2023,  1.1453])\n",
      "\tparams: tensor([  4.1787, -10.5742])\n",
      "Epoch: 564,Loss: 6.895452\n",
      "\tgrad: tensor([-0.2020,  1.1434])\n",
      "\tparams: tensor([  4.1808, -10.5857])\n",
      "Epoch: 565,Loss: 6.881980\n",
      "\tgrad: tensor([-0.2016,  1.1414])\n",
      "\tparams: tensor([  4.1828, -10.5971])\n",
      "Epoch: 566,Loss: 6.868559\n",
      "\tgrad: tensor([-0.2013,  1.1395])\n",
      "\tparams: tensor([  4.1848, -10.6085])\n",
      "Epoch: 567,Loss: 6.855180\n",
      "\tgrad: tensor([-0.2010,  1.1375])\n",
      "\tparams: tensor([  4.1868, -10.6198])\n",
      "Epoch: 568,Loss: 6.841848\n",
      "\tgrad: tensor([-0.2006,  1.1356])\n",
      "\tparams: tensor([  4.1888, -10.6312])\n",
      "Epoch: 569,Loss: 6.828561\n",
      "\tgrad: tensor([-0.2003,  1.1337])\n",
      "\tparams: tensor([  4.1908, -10.6425])\n",
      "Epoch: 570,Loss: 6.815319\n",
      "\tgrad: tensor([-0.1999,  1.1318])\n",
      "\tparams: tensor([  4.1928, -10.6539])\n",
      "Epoch: 571,Loss: 6.802118\n",
      "\tgrad: tensor([-0.1996,  1.1298])\n",
      "\tparams: tensor([  4.1948, -10.6652])\n",
      "Epoch: 572,Loss: 6.788968\n",
      "\tgrad: tensor([-0.1993,  1.1279])\n",
      "\tparams: tensor([  4.1968, -10.6764])\n",
      "Epoch: 573,Loss: 6.775864\n",
      "\tgrad: tensor([-0.1989,  1.1260])\n",
      "\tparams: tensor([  4.1988, -10.6877])\n",
      "Epoch: 574,Loss: 6.762797\n",
      "\tgrad: tensor([-0.1986,  1.1241])\n",
      "\tparams: tensor([  4.2008, -10.6989])\n",
      "Epoch: 575,Loss: 6.749779\n",
      "\tgrad: tensor([-0.1982,  1.1222])\n",
      "\tparams: tensor([  4.2028, -10.7102])\n",
      "Epoch: 576,Loss: 6.736804\n",
      "\tgrad: tensor([-0.1979,  1.1203])\n",
      "\tparams: tensor([  4.2047, -10.7214])\n",
      "Epoch: 577,Loss: 6.723876\n",
      "\tgrad: tensor([-0.1976,  1.1184])\n",
      "\tparams: tensor([  4.2067, -10.7325])\n",
      "Epoch: 578,Loss: 6.710987\n",
      "\tgrad: tensor([-0.1972,  1.1165])\n",
      "\tparams: tensor([  4.2087, -10.7437])\n",
      "Epoch: 579,Loss: 6.698142\n",
      "\tgrad: tensor([-0.1969,  1.1146])\n",
      "\tparams: tensor([  4.2107, -10.7549])\n",
      "Epoch: 580,Loss: 6.685345\n",
      "\tgrad: tensor([-0.1966,  1.1127])\n",
      "\tparams: tensor([  4.2126, -10.7660])\n",
      "Epoch: 581,Loss: 6.672589\n",
      "\tgrad: tensor([-0.1962,  1.1108])\n",
      "\tparams: tensor([  4.2146, -10.7771])\n",
      "Epoch: 582,Loss: 6.659873\n",
      "\tgrad: tensor([-0.1959,  1.1089])\n",
      "\tparams: tensor([  4.2165, -10.7882])\n",
      "Epoch: 583,Loss: 6.647207\n",
      "\tgrad: tensor([-0.1956,  1.1070])\n",
      "\tparams: tensor([  4.2185, -10.7992])\n",
      "Epoch: 584,Loss: 6.634578\n",
      "\tgrad: tensor([-0.1952,  1.1051])\n",
      "\tparams: tensor([  4.2204, -10.8103])\n",
      "Epoch: 585,Loss: 6.621994\n",
      "\tgrad: tensor([-0.1949,  1.1033])\n",
      "\tparams: tensor([  4.2224, -10.8213])\n",
      "Epoch: 586,Loss: 6.609454\n",
      "\tgrad: tensor([-0.1946,  1.1014])\n",
      "\tparams: tensor([  4.2243, -10.8323])\n",
      "Epoch: 587,Loss: 6.596953\n",
      "\tgrad: tensor([-0.1942,  1.0995])\n",
      "\tparams: tensor([  4.2263, -10.8433])\n",
      "Epoch: 588,Loss: 6.584499\n",
      "\tgrad: tensor([-0.1939,  1.0976])\n",
      "\tparams: tensor([  4.2282, -10.8543])\n",
      "Epoch: 589,Loss: 6.572087\n",
      "\tgrad: tensor([-0.1936,  1.0958])\n",
      "\tparams: tensor([  4.2302, -10.8653])\n",
      "Epoch: 590,Loss: 6.559712\n",
      "\tgrad: tensor([-0.1932,  1.0939])\n",
      "\tparams: tensor([  4.2321, -10.8762])\n",
      "Epoch: 591,Loss: 6.547384\n",
      "\tgrad: tensor([-0.1929,  1.0921])\n",
      "\tparams: tensor([  4.2340, -10.8871])\n",
      "Epoch: 592,Loss: 6.535097\n",
      "\tgrad: tensor([-0.1926,  1.0902])\n",
      "\tparams: tensor([  4.2359, -10.8980])\n",
      "Epoch: 593,Loss: 6.522851\n",
      "\tgrad: tensor([-0.1923,  1.0884])\n",
      "\tparams: tensor([  4.2379, -10.9089])\n",
      "Epoch: 594,Loss: 6.510646\n",
      "\tgrad: tensor([-0.1919,  1.0865])\n",
      "\tparams: tensor([  4.2398, -10.9198])\n",
      "Epoch: 595,Loss: 6.498482\n",
      "\tgrad: tensor([-0.1916,  1.0847])\n",
      "\tparams: tensor([  4.2417, -10.9306])\n",
      "Epoch: 596,Loss: 6.486361\n",
      "\tgrad: tensor([-0.1913,  1.0828])\n",
      "\tparams: tensor([  4.2436, -10.9415])\n",
      "Epoch: 597,Loss: 6.474282\n",
      "\tgrad: tensor([-0.1910,  1.0810])\n",
      "\tparams: tensor([  4.2455, -10.9523])\n",
      "Epoch: 598,Loss: 6.462241\n",
      "\tgrad: tensor([-0.1906,  1.0791])\n",
      "\tparams: tensor([  4.2474, -10.9631])\n",
      "Epoch: 599,Loss: 6.450243\n",
      "\tgrad: tensor([-0.1903,  1.0773])\n",
      "\tparams: tensor([  4.2493, -10.9738])\n",
      "Epoch: 600,Loss: 6.438284\n",
      "\tgrad: tensor([-0.1900,  1.0755])\n",
      "\tparams: tensor([  4.2512, -10.9846])\n",
      "Epoch: 601,Loss: 6.426368\n",
      "\tgrad: tensor([-0.1897,  1.0737])\n",
      "\tparams: tensor([  4.2531, -10.9953])\n",
      "Epoch: 602,Loss: 6.414490\n",
      "\tgrad: tensor([-0.1893,  1.0718])\n",
      "\tparams: tensor([  4.2550, -11.0060])\n",
      "Epoch: 603,Loss: 6.402653\n",
      "\tgrad: tensor([-0.1890,  1.0700])\n",
      "\tparams: tensor([  4.2569, -11.0167])\n",
      "Epoch: 604,Loss: 6.390859\n",
      "\tgrad: tensor([-0.1887,  1.0682])\n",
      "\tparams: tensor([  4.2588, -11.0274])\n",
      "Epoch: 605,Loss: 6.379103\n",
      "\tgrad: tensor([-0.1884,  1.0664])\n",
      "\tparams: tensor([  4.2607, -11.0381])\n",
      "Epoch: 606,Loss: 6.367385\n",
      "\tgrad: tensor([-0.1880,  1.0646])\n",
      "\tparams: tensor([  4.2626, -11.0487])\n",
      "Epoch: 607,Loss: 6.355706\n",
      "\tgrad: tensor([-0.1877,  1.0628])\n",
      "\tparams: tensor([  4.2644, -11.0594])\n",
      "Epoch: 608,Loss: 6.344070\n",
      "\tgrad: tensor([-0.1874,  1.0609])\n",
      "\tparams: tensor([  4.2663, -11.0700])\n",
      "Epoch: 609,Loss: 6.332472\n",
      "\tgrad: tensor([-0.1871,  1.0591])\n",
      "\tparams: tensor([  4.2682, -11.0806])\n",
      "Epoch: 610,Loss: 6.320912\n",
      "\tgrad: tensor([-0.1868,  1.0573])\n",
      "\tparams: tensor([  4.2701, -11.0911])\n",
      "Epoch: 611,Loss: 6.309395\n",
      "\tgrad: tensor([-0.1865,  1.0555])\n",
      "\tparams: tensor([  4.2719, -11.1017])\n",
      "Epoch: 612,Loss: 6.297915\n",
      "\tgrad: tensor([-0.1861,  1.0538])\n",
      "\tparams: tensor([  4.2738, -11.1122])\n",
      "Epoch: 613,Loss: 6.286473\n",
      "\tgrad: tensor([-0.1858,  1.0520])\n",
      "\tparams: tensor([  4.2756, -11.1227])\n",
      "Epoch: 614,Loss: 6.275074\n",
      "\tgrad: tensor([-0.1855,  1.0502])\n",
      "\tparams: tensor([  4.2775, -11.1333])\n",
      "Epoch: 615,Loss: 6.263708\n",
      "\tgrad: tensor([-0.1852,  1.0484])\n",
      "\tparams: tensor([  4.2794, -11.1437])\n",
      "Epoch: 616,Loss: 6.252382\n",
      "\tgrad: tensor([-0.1849,  1.0466])\n",
      "\tparams: tensor([  4.2812, -11.1542])\n",
      "Epoch: 617,Loss: 6.241098\n",
      "\tgrad: tensor([-0.1846,  1.0448])\n",
      "\tparams: tensor([  4.2830, -11.1646])\n",
      "Epoch: 618,Loss: 6.229849\n",
      "\tgrad: tensor([-0.1843,  1.0431])\n",
      "\tparams: tensor([  4.2849, -11.1751])\n",
      "Epoch: 619,Loss: 6.218639\n",
      "\tgrad: tensor([-0.1840,  1.0413])\n",
      "\tparams: tensor([  4.2867, -11.1855])\n",
      "Epoch: 620,Loss: 6.207470\n",
      "\tgrad: tensor([-0.1836,  1.0395])\n",
      "\tparams: tensor([  4.2886, -11.1959])\n",
      "Epoch: 621,Loss: 6.196334\n",
      "\tgrad: tensor([-0.1833,  1.0378])\n",
      "\tparams: tensor([  4.2904, -11.2063])\n",
      "Epoch: 622,Loss: 6.185240\n",
      "\tgrad: tensor([-0.1830,  1.0360])\n",
      "\tparams: tensor([  4.2922, -11.2166])\n",
      "Epoch: 623,Loss: 6.174181\n",
      "\tgrad: tensor([-0.1827,  1.0342])\n",
      "\tparams: tensor([  4.2941, -11.2270])\n",
      "Epoch: 624,Loss: 6.163159\n",
      "\tgrad: tensor([-0.1824,  1.0325])\n",
      "\tparams: tensor([  4.2959, -11.2373])\n",
      "Epoch: 625,Loss: 6.152177\n",
      "\tgrad: tensor([-0.1821,  1.0307])\n",
      "\tparams: tensor([  4.2977, -11.2476])\n",
      "Epoch: 626,Loss: 6.141230\n",
      "\tgrad: tensor([-0.1818,  1.0290])\n",
      "\tparams: tensor([  4.2995, -11.2579])\n",
      "Epoch: 627,Loss: 6.130322\n",
      "\tgrad: tensor([-0.1815,  1.0272])\n",
      "\tparams: tensor([  4.3013, -11.2682])\n",
      "Epoch: 628,Loss: 6.119448\n",
      "\tgrad: tensor([-0.1811,  1.0255])\n",
      "\tparams: tensor([  4.3031, -11.2784])\n",
      "Epoch: 629,Loss: 6.108614\n",
      "\tgrad: tensor([-0.1808,  1.0237])\n",
      "\tparams: tensor([  4.3050, -11.2887])\n",
      "Epoch: 630,Loss: 6.097815\n",
      "\tgrad: tensor([-0.1805,  1.0220])\n",
      "\tparams: tensor([  4.3068, -11.2989])\n",
      "Epoch: 631,Loss: 6.087054\n",
      "\tgrad: tensor([-0.1802,  1.0203])\n",
      "\tparams: tensor([  4.3086, -11.3091])\n",
      "Epoch: 632,Loss: 6.076329\n",
      "\tgrad: tensor([-0.1799,  1.0185])\n",
      "\tparams: tensor([  4.3104, -11.3193])\n",
      "Epoch: 633,Loss: 6.065644\n",
      "\tgrad: tensor([-0.1796,  1.0168])\n",
      "\tparams: tensor([  4.3122, -11.3294])\n",
      "Epoch: 634,Loss: 6.054988\n",
      "\tgrad: tensor([-0.1793,  1.0151])\n",
      "\tparams: tensor([  4.3139, -11.3396])\n",
      "Epoch: 635,Loss: 6.044372\n",
      "\tgrad: tensor([-0.1790,  1.0133])\n",
      "\tparams: tensor([  4.3157, -11.3497])\n",
      "Epoch: 636,Loss: 6.033794\n",
      "\tgrad: tensor([-0.1787,  1.0116])\n",
      "\tparams: tensor([  4.3175, -11.3598])\n",
      "Epoch: 637,Loss: 6.023247\n",
      "\tgrad: tensor([-0.1784,  1.0099])\n",
      "\tparams: tensor([  4.3193, -11.3699])\n",
      "Epoch: 638,Loss: 6.012738\n",
      "\tgrad: tensor([-0.1781,  1.0082])\n",
      "\tparams: tensor([  4.3211, -11.3800])\n",
      "Epoch: 639,Loss: 6.002264\n",
      "\tgrad: tensor([-0.1778,  1.0065])\n",
      "\tparams: tensor([  4.3229, -11.3901])\n",
      "Epoch: 640,Loss: 5.991828\n",
      "\tgrad: tensor([-0.1775,  1.0048])\n",
      "\tparams: tensor([  4.3246, -11.4001])\n",
      "Epoch: 641,Loss: 5.981425\n",
      "\tgrad: tensor([-0.1772,  1.0031])\n",
      "\tparams: tensor([  4.3264, -11.4102])\n",
      "Epoch: 642,Loss: 5.971058\n",
      "\tgrad: tensor([-0.1769,  1.0014])\n",
      "\tparams: tensor([  4.3282, -11.4202])\n",
      "Epoch: 643,Loss: 5.960727\n",
      "\tgrad: tensor([-0.1766,  0.9997])\n",
      "\tparams: tensor([  4.3300, -11.4302])\n",
      "Epoch: 644,Loss: 5.950432\n",
      "\tgrad: tensor([-0.1763,  0.9980])\n",
      "\tparams: tensor([  4.3317, -11.4401])\n",
      "Epoch: 645,Loss: 5.940171\n",
      "\tgrad: tensor([-0.1760,  0.9963])\n",
      "\tparams: tensor([  4.3335, -11.4501])\n",
      "Epoch: 646,Loss: 5.929944\n",
      "\tgrad: tensor([-0.1757,  0.9946])\n",
      "\tparams: tensor([  4.3352, -11.4601])\n",
      "Epoch: 647,Loss: 5.919752\n",
      "\tgrad: tensor([-0.1754,  0.9929])\n",
      "\tparams: tensor([  4.3370, -11.4700])\n",
      "Epoch: 648,Loss: 5.909596\n",
      "\tgrad: tensor([-0.1751,  0.9912])\n",
      "\tparams: tensor([  4.3387, -11.4799])\n",
      "Epoch: 649,Loss: 5.899472\n",
      "\tgrad: tensor([-0.1748,  0.9895])\n",
      "\tparams: tensor([  4.3405, -11.4898])\n",
      "Epoch: 650,Loss: 5.889383\n",
      "\tgrad: tensor([-0.1745,  0.9878])\n",
      "\tparams: tensor([  4.3422, -11.4997])\n",
      "Epoch: 651,Loss: 5.879326\n",
      "\tgrad: tensor([-0.1742,  0.9862])\n",
      "\tparams: tensor([  4.3440, -11.5095])\n",
      "Epoch: 652,Loss: 5.869310\n",
      "\tgrad: tensor([-0.1739,  0.9845])\n",
      "\tparams: tensor([  4.3457, -11.5194])\n",
      "Epoch: 653,Loss: 5.859322\n",
      "\tgrad: tensor([-0.1736,  0.9828])\n",
      "\tparams: tensor([  4.3474, -11.5292])\n",
      "Epoch: 654,Loss: 5.849374\n",
      "\tgrad: tensor([-0.1733,  0.9811])\n",
      "\tparams: tensor([  4.3492, -11.5390])\n",
      "Epoch: 655,Loss: 5.839453\n",
      "\tgrad: tensor([-0.1730,  0.9795])\n",
      "\tparams: tensor([  4.3509, -11.5488])\n",
      "Epoch: 656,Loss: 5.829570\n",
      "\tgrad: tensor([-0.1727,  0.9778])\n",
      "\tparams: tensor([  4.3526, -11.5586])\n",
      "Epoch: 657,Loss: 5.819718\n",
      "\tgrad: tensor([-0.1724,  0.9761])\n",
      "\tparams: tensor([  4.3544, -11.5683])\n",
      "Epoch: 658,Loss: 5.809901\n",
      "\tgrad: tensor([-0.1722,  0.9745])\n",
      "\tparams: tensor([  4.3561, -11.5781])\n",
      "Epoch: 659,Loss: 5.800116\n",
      "\tgrad: tensor([-0.1719,  0.9728])\n",
      "\tparams: tensor([  4.3578, -11.5878])\n",
      "Epoch: 660,Loss: 5.790367\n",
      "\tgrad: tensor([-0.1716,  0.9712])\n",
      "\tparams: tensor([  4.3595, -11.5975])\n",
      "Epoch: 661,Loss: 5.780646\n",
      "\tgrad: tensor([-0.1713,  0.9695])\n",
      "\tparams: tensor([  4.3612, -11.6072])\n",
      "Epoch: 662,Loss: 5.770962\n",
      "\tgrad: tensor([-0.1710,  0.9679])\n",
      "\tparams: tensor([  4.3629, -11.6169])\n",
      "Epoch: 663,Loss: 5.761312\n",
      "\tgrad: tensor([-0.1707,  0.9662])\n",
      "\tparams: tensor([  4.3646, -11.6266])\n",
      "Epoch: 664,Loss: 5.751694\n",
      "\tgrad: tensor([-0.1704,  0.9646])\n",
      "\tparams: tensor([  4.3664, -11.6362])\n",
      "Epoch: 665,Loss: 5.742105\n",
      "\tgrad: tensor([-0.1701,  0.9630])\n",
      "\tparams: tensor([  4.3681, -11.6458])\n",
      "Epoch: 666,Loss: 5.732550\n",
      "\tgrad: tensor([-0.1698,  0.9613])\n",
      "\tparams: tensor([  4.3697, -11.6555])\n",
      "Epoch: 667,Loss: 5.723031\n",
      "\tgrad: tensor([-0.1695,  0.9597])\n",
      "\tparams: tensor([  4.3714, -11.6651])\n",
      "Epoch: 668,Loss: 5.713540\n",
      "\tgrad: tensor([-0.1692,  0.9581])\n",
      "\tparams: tensor([  4.3731, -11.6746])\n",
      "Epoch: 669,Loss: 5.704083\n",
      "\tgrad: tensor([-0.1690,  0.9564])\n",
      "\tparams: tensor([  4.3748, -11.6842])\n",
      "Epoch: 670,Loss: 5.694659\n",
      "\tgrad: tensor([-0.1687,  0.9548])\n",
      "\tparams: tensor([  4.3765, -11.6937])\n",
      "Epoch: 671,Loss: 5.685266\n",
      "\tgrad: tensor([-0.1684,  0.9532])\n",
      "\tparams: tensor([  4.3782, -11.7033])\n",
      "Epoch: 672,Loss: 5.675904\n",
      "\tgrad: tensor([-0.1681,  0.9516])\n",
      "\tparams: tensor([  4.3799, -11.7128])\n",
      "Epoch: 673,Loss: 5.666573\n",
      "\tgrad: tensor([-0.1678,  0.9499])\n",
      "\tparams: tensor([  4.3816, -11.7223])\n",
      "Epoch: 674,Loss: 5.657277\n",
      "\tgrad: tensor([-0.1675,  0.9483])\n",
      "\tparams: tensor([  4.3832, -11.7318])\n",
      "Epoch: 675,Loss: 5.648010\n",
      "\tgrad: tensor([-0.1673,  0.9467])\n",
      "\tparams: tensor([  4.3849, -11.7412])\n",
      "Epoch: 676,Loss: 5.638776\n",
      "\tgrad: tensor([-0.1670,  0.9451])\n",
      "\tparams: tensor([  4.3866, -11.7507])\n",
      "Epoch: 677,Loss: 5.629574\n",
      "\tgrad: tensor([-0.1667,  0.9435])\n",
      "\tparams: tensor([  4.3882, -11.7601])\n",
      "Epoch: 678,Loss: 5.620402\n",
      "\tgrad: tensor([-0.1664,  0.9419])\n",
      "\tparams: tensor([  4.3899, -11.7696])\n",
      "Epoch: 679,Loss: 5.611260\n",
      "\tgrad: tensor([-0.1661,  0.9403])\n",
      "\tparams: tensor([  4.3916, -11.7790])\n",
      "Epoch: 680,Loss: 5.602149\n",
      "\tgrad: tensor([-0.1658,  0.9387])\n",
      "\tparams: tensor([  4.3932, -11.7883])\n",
      "Epoch: 681,Loss: 5.593071\n",
      "\tgrad: tensor([-0.1656,  0.9371])\n",
      "\tparams: tensor([  4.3949, -11.7977])\n",
      "Epoch: 682,Loss: 5.584022\n",
      "\tgrad: tensor([-0.1653,  0.9355])\n",
      "\tparams: tensor([  4.3965, -11.8071])\n",
      "Epoch: 683,Loss: 5.575005\n",
      "\tgrad: tensor([-0.1650,  0.9339])\n",
      "\tparams: tensor([  4.3982, -11.8164])\n",
      "Epoch: 684,Loss: 5.566019\n",
      "\tgrad: tensor([-0.1647,  0.9323])\n",
      "\tparams: tensor([  4.3998, -11.8257])\n",
      "Epoch: 685,Loss: 5.557063\n",
      "\tgrad: tensor([-0.1644,  0.9308])\n",
      "\tparams: tensor([  4.4015, -11.8350])\n",
      "Epoch: 686,Loss: 5.548136\n",
      "\tgrad: tensor([-0.1641,  0.9292])\n",
      "\tparams: tensor([  4.4031, -11.8443])\n",
      "Epoch: 687,Loss: 5.539241\n",
      "\tgrad: tensor([-0.1639,  0.9276])\n",
      "\tparams: tensor([  4.4048, -11.8536])\n",
      "Epoch: 688,Loss: 5.530376\n",
      "\tgrad: tensor([-0.1636,  0.9260])\n",
      "\tparams: tensor([  4.4064, -11.8629])\n",
      "Epoch: 689,Loss: 5.521540\n",
      "\tgrad: tensor([-0.1633,  0.9245])\n",
      "\tparams: tensor([  4.4080, -11.8721])\n",
      "Epoch: 690,Loss: 5.512734\n",
      "\tgrad: tensor([-0.1630,  0.9229])\n",
      "\tparams: tensor([  4.4097, -11.8813])\n",
      "Epoch: 691,Loss: 5.503958\n",
      "\tgrad: tensor([-0.1628,  0.9213])\n",
      "\tparams: tensor([  4.4113, -11.8906])\n",
      "Epoch: 692,Loss: 5.495212\n",
      "\tgrad: tensor([-0.1625,  0.9197])\n",
      "\tparams: tensor([  4.4129, -11.8998])\n",
      "Epoch: 693,Loss: 5.486496\n",
      "\tgrad: tensor([-0.1622,  0.9182])\n",
      "\tparams: tensor([  4.4145, -11.9089])\n",
      "Epoch: 694,Loss: 5.477808\n",
      "\tgrad: tensor([-0.1619,  0.9166])\n",
      "\tparams: tensor([  4.4161, -11.9181])\n",
      "Epoch: 695,Loss: 5.469152\n",
      "\tgrad: tensor([-0.1617,  0.9151])\n",
      "\tparams: tensor([  4.4178, -11.9272])\n",
      "Epoch: 696,Loss: 5.460525\n",
      "\tgrad: tensor([-0.1614,  0.9135])\n",
      "\tparams: tensor([  4.4194, -11.9364])\n",
      "Epoch: 697,Loss: 5.451928\n",
      "\tgrad: tensor([-0.1611,  0.9120])\n",
      "\tparams: tensor([  4.4210, -11.9455])\n",
      "Epoch: 698,Loss: 5.443358\n",
      "\tgrad: tensor([-0.1608,  0.9104])\n",
      "\tparams: tensor([  4.4226, -11.9546])\n",
      "Epoch: 699,Loss: 5.434819\n",
      "\tgrad: tensor([-0.1605,  0.9089])\n",
      "\tparams: tensor([  4.4242, -11.9637])\n",
      "Epoch: 700,Loss: 5.426309\n",
      "\tgrad: tensor([-0.1603,  0.9073])\n",
      "\tparams: tensor([  4.4258, -11.9728])\n",
      "Epoch: 701,Loss: 5.417827\n",
      "\tgrad: tensor([-0.1600,  0.9058])\n",
      "\tparams: tensor([  4.4274, -11.9818])\n",
      "Epoch: 702,Loss: 5.409372\n",
      "\tgrad: tensor([-0.1597,  0.9042])\n",
      "\tparams: tensor([  4.4290, -11.9909])\n",
      "Epoch: 703,Loss: 5.400949\n",
      "\tgrad: tensor([-0.1595,  0.9027])\n",
      "\tparams: tensor([  4.4306, -11.9999])\n",
      "Epoch: 704,Loss: 5.392550\n",
      "\tgrad: tensor([-0.1592,  0.9012])\n",
      "\tparams: tensor([  4.4322, -12.0089])\n",
      "Epoch: 705,Loss: 5.384184\n",
      "\tgrad: tensor([-0.1589,  0.8996])\n",
      "\tparams: tensor([  4.4338, -12.0179])\n",
      "Epoch: 706,Loss: 5.375846\n",
      "\tgrad: tensor([-0.1586,  0.8981])\n",
      "\tparams: tensor([  4.4354, -12.0269])\n",
      "Epoch: 707,Loss: 5.367537\n",
      "\tgrad: tensor([-0.1584,  0.8966])\n",
      "\tparams: tensor([  4.4369, -12.0359])\n",
      "Epoch: 708,Loss: 5.359253\n",
      "\tgrad: tensor([-0.1581,  0.8951])\n",
      "\tparams: tensor([  4.4385, -12.0448])\n",
      "Epoch: 709,Loss: 5.350999\n",
      "\tgrad: tensor([-0.1578,  0.8935])\n",
      "\tparams: tensor([  4.4401, -12.0537])\n",
      "Epoch: 710,Loss: 5.342772\n",
      "\tgrad: tensor([-0.1576,  0.8920])\n",
      "\tparams: tensor([  4.4417, -12.0627])\n",
      "Epoch: 711,Loss: 5.334575\n",
      "\tgrad: tensor([-0.1573,  0.8905])\n",
      "\tparams: tensor([  4.4433, -12.0716])\n",
      "Epoch: 712,Loss: 5.326402\n",
      "\tgrad: tensor([-0.1570,  0.8890])\n",
      "\tparams: tensor([  4.4448, -12.0805])\n",
      "Epoch: 713,Loss: 5.318260\n",
      "\tgrad: tensor([-0.1568,  0.8875])\n",
      "\tparams: tensor([  4.4464, -12.0893])\n",
      "Epoch: 714,Loss: 5.310144\n",
      "\tgrad: tensor([-0.1565,  0.8860])\n",
      "\tparams: tensor([  4.4480, -12.0982])\n",
      "Epoch: 715,Loss: 5.302055\n",
      "\tgrad: tensor([-0.1562,  0.8845])\n",
      "\tparams: tensor([  4.4495, -12.1070])\n",
      "Epoch: 716,Loss: 5.293994\n",
      "\tgrad: tensor([-0.1560,  0.8830])\n",
      "\tparams: tensor([  4.4511, -12.1159])\n",
      "Epoch: 717,Loss: 5.285964\n",
      "\tgrad: tensor([-0.1557,  0.8815])\n",
      "\tparams: tensor([  4.4526, -12.1247])\n",
      "Epoch: 718,Loss: 5.277958\n",
      "\tgrad: tensor([-0.1555,  0.8800])\n",
      "\tparams: tensor([  4.4542, -12.1335])\n",
      "Epoch: 719,Loss: 5.269979\n",
      "\tgrad: tensor([-0.1552,  0.8785])\n",
      "\tparams: tensor([  4.4557, -12.1423])\n",
      "Epoch: 720,Loss: 5.262027\n",
      "\tgrad: tensor([-0.1549,  0.8770])\n",
      "\tparams: tensor([  4.4573, -12.1510])\n",
      "Epoch: 721,Loss: 5.254103\n",
      "\tgrad: tensor([-0.1547,  0.8755])\n",
      "\tparams: tensor([  4.4588, -12.1598])\n",
      "Epoch: 722,Loss: 5.246205\n",
      "\tgrad: tensor([-0.1544,  0.8740])\n",
      "\tparams: tensor([  4.4604, -12.1685])\n",
      "Epoch: 723,Loss: 5.238335\n",
      "\tgrad: tensor([-0.1541,  0.8725])\n",
      "\tparams: tensor([  4.4619, -12.1773])\n",
      "Epoch: 724,Loss: 5.230492\n",
      "\tgrad: tensor([-0.1539,  0.8710])\n",
      "\tparams: tensor([  4.4635, -12.1860])\n",
      "Epoch: 725,Loss: 5.222674\n",
      "\tgrad: tensor([-0.1536,  0.8696])\n",
      "\tparams: tensor([  4.4650, -12.1947])\n",
      "Epoch: 726,Loss: 5.214881\n",
      "\tgrad: tensor([-0.1533,  0.8681])\n",
      "\tparams: tensor([  4.4665, -12.2033])\n",
      "Epoch: 727,Loss: 5.207120\n",
      "\tgrad: tensor([-0.1531,  0.8666])\n",
      "\tparams: tensor([  4.4681, -12.2120])\n",
      "Epoch: 728,Loss: 5.199381\n",
      "\tgrad: tensor([-0.1528,  0.8651])\n",
      "\tparams: tensor([  4.4696, -12.2207])\n",
      "Epoch: 729,Loss: 5.191670\n",
      "\tgrad: tensor([-0.1526,  0.8637])\n",
      "\tparams: tensor([  4.4711, -12.2293])\n",
      "Epoch: 730,Loss: 5.183985\n",
      "\tgrad: tensor([-0.1523,  0.8622])\n",
      "\tparams: tensor([  4.4726, -12.2379])\n",
      "Epoch: 731,Loss: 5.176324\n",
      "\tgrad: tensor([-0.1520,  0.8607])\n",
      "\tparams: tensor([  4.4742, -12.2465])\n",
      "Epoch: 732,Loss: 5.168688\n",
      "\tgrad: tensor([-0.1518,  0.8593])\n",
      "\tparams: tensor([  4.4757, -12.2551])\n",
      "Epoch: 733,Loss: 5.161084\n",
      "\tgrad: tensor([-0.1515,  0.8578])\n",
      "\tparams: tensor([  4.4772, -12.2637])\n",
      "Epoch: 734,Loss: 5.153500\n",
      "\tgrad: tensor([-0.1513,  0.8564])\n",
      "\tparams: tensor([  4.4787, -12.2723])\n",
      "Epoch: 735,Loss: 5.145944\n",
      "\tgrad: tensor([-0.1510,  0.8549])\n",
      "\tparams: tensor([  4.4802, -12.2808])\n",
      "Epoch: 736,Loss: 5.138413\n",
      "\tgrad: tensor([-0.1508,  0.8535])\n",
      "\tparams: tensor([  4.4817, -12.2893])\n",
      "Epoch: 737,Loss: 5.130910\n",
      "\tgrad: tensor([-0.1505,  0.8520])\n",
      "\tparams: tensor([  4.4832, -12.2979])\n",
      "Epoch: 738,Loss: 5.123428\n",
      "\tgrad: tensor([-0.1502,  0.8506])\n",
      "\tparams: tensor([  4.4847, -12.3064])\n",
      "Epoch: 739,Loss: 5.115978\n",
      "\tgrad: tensor([-0.1500,  0.8491])\n",
      "\tparams: tensor([  4.4862, -12.3149])\n",
      "Epoch: 740,Loss: 5.108547\n",
      "\tgrad: tensor([-0.1497,  0.8477])\n",
      "\tparams: tensor([  4.4877, -12.3233])\n",
      "Epoch: 741,Loss: 5.101143\n",
      "\tgrad: tensor([-0.1495,  0.8462])\n",
      "\tparams: tensor([  4.4892, -12.3318])\n",
      "Epoch: 742,Loss: 5.093765\n",
      "\tgrad: tensor([-0.1492,  0.8448])\n",
      "\tparams: tensor([  4.4907, -12.3402])\n",
      "Epoch: 743,Loss: 5.086414\n",
      "\tgrad: tensor([-0.1490,  0.8434])\n",
      "\tparams: tensor([  4.4922, -12.3487])\n",
      "Epoch: 744,Loss: 5.079086\n",
      "\tgrad: tensor([-0.1487,  0.8419])\n",
      "\tparams: tensor([  4.4937, -12.3571])\n",
      "Epoch: 745,Loss: 5.071781\n",
      "\tgrad: tensor([-0.1485,  0.8405])\n",
      "\tparams: tensor([  4.4952, -12.3655])\n",
      "Epoch: 746,Loss: 5.064505\n",
      "\tgrad: tensor([-0.1482,  0.8391])\n",
      "\tparams: tensor([  4.4967, -12.3739])\n",
      "Epoch: 747,Loss: 5.057247\n",
      "\tgrad: tensor([-0.1480,  0.8376])\n",
      "\tparams: tensor([  4.4981, -12.3823])\n",
      "Epoch: 748,Loss: 5.050021\n",
      "\tgrad: tensor([-0.1477,  0.8362])\n",
      "\tparams: tensor([  4.4996, -12.3906])\n",
      "Epoch: 749,Loss: 5.042817\n",
      "\tgrad: tensor([-0.1475,  0.8348])\n",
      "\tparams: tensor([  4.5011, -12.3990])\n",
      "Epoch: 750,Loss: 5.035636\n",
      "\tgrad: tensor([-0.1472,  0.8334])\n",
      "\tparams: tensor([  4.5026, -12.4073])\n",
      "Epoch: 751,Loss: 5.028476\n",
      "\tgrad: tensor([-0.1470,  0.8320])\n",
      "\tparams: tensor([  4.5040, -12.4156])\n",
      "Epoch: 752,Loss: 5.021346\n",
      "\tgrad: tensor([-0.1467,  0.8305])\n",
      "\tparams: tensor([  4.5055, -12.4239])\n",
      "Epoch: 753,Loss: 5.014240\n",
      "\tgrad: tensor([-0.1465,  0.8291])\n",
      "\tparams: tensor([  4.5070, -12.4322])\n",
      "Epoch: 754,Loss: 5.007157\n",
      "\tgrad: tensor([-0.1462,  0.8277])\n",
      "\tparams: tensor([  4.5084, -12.4405])\n",
      "Epoch: 755,Loss: 5.000099\n",
      "\tgrad: tensor([-0.1460,  0.8263])\n",
      "\tparams: tensor([  4.5099, -12.4488])\n",
      "Epoch: 756,Loss: 4.993064\n",
      "\tgrad: tensor([-0.1457,  0.8249])\n",
      "\tparams: tensor([  4.5113, -12.4570])\n",
      "Epoch: 757,Loss: 4.986051\n",
      "\tgrad: tensor([-0.1455,  0.8235])\n",
      "\tparams: tensor([  4.5128, -12.4653])\n",
      "Epoch: 758,Loss: 4.979064\n",
      "\tgrad: tensor([-0.1452,  0.8221])\n",
      "\tparams: tensor([  4.5143, -12.4735])\n",
      "Epoch: 759,Loss: 4.972100\n",
      "\tgrad: tensor([-0.1450,  0.8207])\n",
      "\tparams: tensor([  4.5157, -12.4817])\n",
      "Epoch: 760,Loss: 4.965159\n",
      "\tgrad: tensor([-0.1447,  0.8193])\n",
      "\tparams: tensor([  4.5172, -12.4899])\n",
      "Epoch: 761,Loss: 4.958245\n",
      "\tgrad: tensor([-0.1445,  0.8179])\n",
      "\tparams: tensor([  4.5186, -12.4981])\n",
      "Epoch: 762,Loss: 4.951351\n",
      "\tgrad: tensor([-0.1443,  0.8165])\n",
      "\tparams: tensor([  4.5200, -12.5062])\n",
      "Epoch: 763,Loss: 4.944479\n",
      "\tgrad: tensor([-0.1440,  0.8152])\n",
      "\tparams: tensor([  4.5215, -12.5144])\n",
      "Epoch: 764,Loss: 4.937633\n",
      "\tgrad: tensor([-0.1438,  0.8138])\n",
      "\tparams: tensor([  4.5229, -12.5225])\n",
      "Epoch: 765,Loss: 4.930812\n",
      "\tgrad: tensor([-0.1435,  0.8124])\n",
      "\tparams: tensor([  4.5244, -12.5306])\n",
      "Epoch: 766,Loss: 4.924009\n",
      "\tgrad: tensor([-0.1433,  0.8110])\n",
      "\tparams: tensor([  4.5258, -12.5387])\n",
      "Epoch: 767,Loss: 4.917234\n",
      "\tgrad: tensor([-0.1430,  0.8096])\n",
      "\tparams: tensor([  4.5272, -12.5468])\n",
      "Epoch: 768,Loss: 4.910480\n",
      "\tgrad: tensor([-0.1428,  0.8083])\n",
      "\tparams: tensor([  4.5286, -12.5549])\n",
      "Epoch: 769,Loss: 4.903749\n",
      "\tgrad: tensor([-0.1426,  0.8069])\n",
      "\tparams: tensor([  4.5301, -12.5630])\n",
      "Epoch: 770,Loss: 4.897040\n",
      "\tgrad: tensor([-0.1423,  0.8055])\n",
      "\tparams: tensor([  4.5315, -12.5711])\n",
      "Epoch: 771,Loss: 4.890356\n",
      "\tgrad: tensor([-0.1420,  0.8042])\n",
      "\tparams: tensor([  4.5329, -12.5791])\n",
      "Epoch: 772,Loss: 4.883692\n",
      "\tgrad: tensor([-0.1418,  0.8028])\n",
      "\tparams: tensor([  4.5343, -12.5871])\n",
      "Epoch: 773,Loss: 4.877052\n",
      "\tgrad: tensor([-0.1416,  0.8014])\n",
      "\tparams: tensor([  4.5357, -12.5951])\n",
      "Epoch: 774,Loss: 4.870436\n",
      "\tgrad: tensor([-0.1413,  0.8001])\n",
      "\tparams: tensor([  4.5372, -12.6031])\n",
      "Epoch: 775,Loss: 4.863839\n",
      "\tgrad: tensor([-0.1411,  0.7987])\n",
      "\tparams: tensor([  4.5386, -12.6111])\n",
      "Epoch: 776,Loss: 4.857268\n",
      "\tgrad: tensor([-0.1408,  0.7973])\n",
      "\tparams: tensor([  4.5400, -12.6191])\n",
      "Epoch: 777,Loss: 4.850718\n",
      "\tgrad: tensor([-0.1406,  0.7960])\n",
      "\tparams: tensor([  4.5414, -12.6271])\n",
      "Epoch: 778,Loss: 4.844189\n",
      "\tgrad: tensor([-0.1404,  0.7946])\n",
      "\tparams: tensor([  4.5428, -12.6350])\n",
      "Epoch: 779,Loss: 4.837683\n",
      "\tgrad: tensor([-0.1401,  0.7933])\n",
      "\tparams: tensor([  4.5442, -12.6429])\n",
      "Epoch: 780,Loss: 4.831196\n",
      "\tgrad: tensor([-0.1399,  0.7919])\n",
      "\tparams: tensor([  4.5456, -12.6509])\n",
      "Epoch: 781,Loss: 4.824737\n",
      "\tgrad: tensor([-0.1397,  0.7906])\n",
      "\tparams: tensor([  4.5470, -12.6588])\n",
      "Epoch: 782,Loss: 4.818298\n",
      "\tgrad: tensor([-0.1394,  0.7893])\n",
      "\tparams: tensor([  4.5484, -12.6667])\n",
      "Epoch: 783,Loss: 4.811879\n",
      "\tgrad: tensor([-0.1392,  0.7879])\n",
      "\tparams: tensor([  4.5498, -12.6745])\n",
      "Epoch: 784,Loss: 4.805481\n",
      "\tgrad: tensor([-0.1389,  0.7866])\n",
      "\tparams: tensor([  4.5512, -12.6824])\n",
      "Epoch: 785,Loss: 4.799106\n",
      "\tgrad: tensor([-0.1387,  0.7852])\n",
      "\tparams: tensor([  4.5525, -12.6902])\n",
      "Epoch: 786,Loss: 4.792755\n",
      "\tgrad: tensor([-0.1385,  0.7839])\n",
      "\tparams: tensor([  4.5539, -12.6981])\n",
      "Epoch: 787,Loss: 4.786422\n",
      "\tgrad: tensor([-0.1383,  0.7826])\n",
      "\tparams: tensor([  4.5553, -12.7059])\n",
      "Epoch: 788,Loss: 4.780112\n",
      "\tgrad: tensor([-0.1380,  0.7812])\n",
      "\tparams: tensor([  4.5567, -12.7137])\n",
      "Epoch: 789,Loss: 4.773824\n",
      "\tgrad: tensor([-0.1378,  0.7799])\n",
      "\tparams: tensor([  4.5581, -12.7215])\n",
      "Epoch: 790,Loss: 4.767558\n",
      "\tgrad: tensor([-0.1375,  0.7786])\n",
      "\tparams: tensor([  4.5594, -12.7293])\n",
      "Epoch: 791,Loss: 4.761312\n",
      "\tgrad: tensor([-0.1373,  0.7773])\n",
      "\tparams: tensor([  4.5608, -12.7371])\n",
      "Epoch: 792,Loss: 4.755087\n",
      "\tgrad: tensor([-0.1371,  0.7759])\n",
      "\tparams: tensor([  4.5622, -12.7448])\n",
      "Epoch: 793,Loss: 4.748885\n",
      "\tgrad: tensor([-0.1368,  0.7746])\n",
      "\tparams: tensor([  4.5636, -12.7526])\n",
      "Epoch: 794,Loss: 4.742700\n",
      "\tgrad: tensor([-0.1366,  0.7733])\n",
      "\tparams: tensor([  4.5649, -12.7603])\n",
      "Epoch: 795,Loss: 4.736537\n",
      "\tgrad: tensor([-0.1364,  0.7720])\n",
      "\tparams: tensor([  4.5663, -12.7680])\n",
      "Epoch: 796,Loss: 4.730397\n",
      "\tgrad: tensor([-0.1361,  0.7707])\n",
      "\tparams: tensor([  4.5677, -12.7758])\n",
      "Epoch: 797,Loss: 4.724279\n",
      "\tgrad: tensor([-0.1359,  0.7694])\n",
      "\tparams: tensor([  4.5690, -12.7834])\n",
      "Epoch: 798,Loss: 4.718181\n",
      "\tgrad: tensor([-0.1357,  0.7681])\n",
      "\tparams: tensor([  4.5704, -12.7911])\n",
      "Epoch: 799,Loss: 4.712101\n",
      "\tgrad: tensor([-0.1354,  0.7668])\n",
      "\tparams: tensor([  4.5717, -12.7988])\n",
      "Epoch: 800,Loss: 4.706046\n",
      "\tgrad: tensor([-0.1352,  0.7655])\n",
      "\tparams: tensor([  4.5731, -12.8064])\n",
      "Epoch: 801,Loss: 4.700009\n",
      "\tgrad: tensor([-0.1350,  0.7642])\n",
      "\tparams: tensor([  4.5744, -12.8141])\n",
      "Epoch: 802,Loss: 4.693990\n",
      "\tgrad: tensor([-0.1347,  0.7629])\n",
      "\tparams: tensor([  4.5758, -12.8217])\n",
      "Epoch: 803,Loss: 4.687995\n",
      "\tgrad: tensor([-0.1345,  0.7616])\n",
      "\tparams: tensor([  4.5771, -12.8293])\n",
      "Epoch: 804,Loss: 4.682020\n",
      "\tgrad: tensor([-0.1343,  0.7603])\n",
      "\tparams: tensor([  4.5785, -12.8369])\n",
      "Epoch: 805,Loss: 4.676063\n",
      "\tgrad: tensor([-0.1341,  0.7590])\n",
      "\tparams: tensor([  4.5798, -12.8445])\n",
      "Epoch: 806,Loss: 4.670130\n",
      "\tgrad: tensor([-0.1338,  0.7577])\n",
      "\tparams: tensor([  4.5811, -12.8521])\n",
      "Epoch: 807,Loss: 4.664214\n",
      "\tgrad: tensor([-0.1336,  0.7564])\n",
      "\tparams: tensor([  4.5825, -12.8597])\n",
      "Epoch: 808,Loss: 4.658319\n",
      "\tgrad: tensor([-0.1334,  0.7551])\n",
      "\tparams: tensor([  4.5838, -12.8672])\n",
      "Epoch: 809,Loss: 4.652445\n",
      "\tgrad: tensor([-0.1332,  0.7538])\n",
      "\tparams: tensor([  4.5851, -12.8748])\n",
      "Epoch: 810,Loss: 4.646592\n",
      "\tgrad: tensor([-0.1330,  0.7526])\n",
      "\tparams: tensor([  4.5865, -12.8823])\n",
      "Epoch: 811,Loss: 4.640754\n",
      "\tgrad: tensor([-0.1327,  0.7513])\n",
      "\tparams: tensor([  4.5878, -12.8898])\n",
      "Epoch: 812,Loss: 4.634938\n",
      "\tgrad: tensor([-0.1325,  0.7500])\n",
      "\tparams: tensor([  4.5891, -12.8973])\n",
      "Epoch: 813,Loss: 4.629142\n",
      "\tgrad: tensor([-0.1323,  0.7487])\n",
      "\tparams: tensor([  4.5904, -12.9048])\n",
      "Epoch: 814,Loss: 4.623367\n",
      "\tgrad: tensor([-0.1320,  0.7475])\n",
      "\tparams: tensor([  4.5918, -12.9123])\n",
      "Epoch: 815,Loss: 4.617611\n",
      "\tgrad: tensor([-0.1318,  0.7462])\n",
      "\tparams: tensor([  4.5931, -12.9197])\n",
      "Epoch: 816,Loss: 4.611872\n",
      "\tgrad: tensor([-0.1316,  0.7449])\n",
      "\tparams: tensor([  4.5944, -12.9272])\n",
      "Epoch: 817,Loss: 4.606156\n",
      "\tgrad: tensor([-0.1314,  0.7437])\n",
      "\tparams: tensor([  4.5957, -12.9346])\n",
      "Epoch: 818,Loss: 4.600458\n",
      "\tgrad: tensor([-0.1311,  0.7424])\n",
      "\tparams: tensor([  4.5970, -12.9420])\n",
      "Epoch: 819,Loss: 4.594780\n",
      "\tgrad: tensor([-0.1309,  0.7411])\n",
      "\tparams: tensor([  4.5983, -12.9494])\n",
      "Epoch: 820,Loss: 4.589119\n",
      "\tgrad: tensor([-0.1307,  0.7399])\n",
      "\tparams: tensor([  4.5996, -12.9568])\n",
      "Epoch: 821,Loss: 4.583479\n",
      "\tgrad: tensor([-0.1305,  0.7386])\n",
      "\tparams: tensor([  4.6009, -12.9642])\n",
      "Epoch: 822,Loss: 4.577857\n",
      "\tgrad: tensor([-0.1303,  0.7374])\n",
      "\tparams: tensor([  4.6022, -12.9716])\n",
      "Epoch: 823,Loss: 4.572256\n",
      "\tgrad: tensor([-0.1300,  0.7361])\n",
      "\tparams: tensor([  4.6035, -12.9790])\n",
      "Epoch: 824,Loss: 4.566675\n",
      "\tgrad: tensor([-0.1298,  0.7349])\n",
      "\tparams: tensor([  4.6048, -12.9863])\n",
      "Epoch: 825,Loss: 4.561108\n",
      "\tgrad: tensor([-0.1296,  0.7336])\n",
      "\tparams: tensor([  4.6061, -12.9936])\n",
      "Epoch: 826,Loss: 4.555565\n",
      "\tgrad: tensor([-0.1294,  0.7324])\n",
      "\tparams: tensor([  4.6074, -13.0010])\n",
      "Epoch: 827,Loss: 4.550039\n",
      "\tgrad: tensor([-0.1292,  0.7311])\n",
      "\tparams: tensor([  4.6087, -13.0083])\n",
      "Epoch: 828,Loss: 4.544534\n",
      "\tgrad: tensor([-0.1289,  0.7299])\n",
      "\tparams: tensor([  4.6100, -13.0156])\n",
      "Epoch: 829,Loss: 4.539044\n",
      "\tgrad: tensor([-0.1287,  0.7286])\n",
      "\tparams: tensor([  4.6113, -13.0229])\n",
      "Epoch: 830,Loss: 4.533575\n",
      "\tgrad: tensor([-0.1285,  0.7274])\n",
      "\tparams: tensor([  4.6126, -13.0301])\n",
      "Epoch: 831,Loss: 4.528122\n",
      "\tgrad: tensor([-0.1283,  0.7262])\n",
      "\tparams: tensor([  4.6139, -13.0374])\n",
      "Epoch: 832,Loss: 4.522691\n",
      "\tgrad: tensor([-0.1280,  0.7249])\n",
      "\tparams: tensor([  4.6152, -13.0446])\n",
      "Epoch: 833,Loss: 4.517276\n",
      "\tgrad: tensor([-0.1278,  0.7237])\n",
      "\tparams: tensor([  4.6164, -13.0519])\n",
      "Epoch: 834,Loss: 4.511879\n",
      "\tgrad: tensor([-0.1276,  0.7225])\n",
      "\tparams: tensor([  4.6177, -13.0591])\n",
      "Epoch: 835,Loss: 4.506505\n",
      "\tgrad: tensor([-0.1274,  0.7212])\n",
      "\tparams: tensor([  4.6190, -13.0663])\n",
      "Epoch: 836,Loss: 4.501141\n",
      "\tgrad: tensor([-0.1272,  0.7200])\n",
      "\tparams: tensor([  4.6203, -13.0735])\n",
      "Epoch: 837,Loss: 4.495801\n",
      "\tgrad: tensor([-0.1270,  0.7188])\n",
      "\tparams: tensor([  4.6215, -13.0807])\n",
      "Epoch: 838,Loss: 4.490475\n",
      "\tgrad: tensor([-0.1268,  0.7176])\n",
      "\tparams: tensor([  4.6228, -13.0879])\n",
      "Epoch: 839,Loss: 4.485169\n",
      "\tgrad: tensor([-0.1266,  0.7163])\n",
      "\tparams: tensor([  4.6241, -13.0950])\n",
      "Epoch: 840,Loss: 4.479884\n",
      "\tgrad: tensor([-0.1263,  0.7151])\n",
      "\tparams: tensor([  4.6253, -13.1022])\n",
      "Epoch: 841,Loss: 4.474613\n",
      "\tgrad: tensor([-0.1261,  0.7139])\n",
      "\tparams: tensor([  4.6266, -13.1093])\n",
      "Epoch: 842,Loss: 4.469364\n",
      "\tgrad: tensor([-0.1259,  0.7127])\n",
      "\tparams: tensor([  4.6278, -13.1165])\n",
      "Epoch: 843,Loss: 4.464130\n",
      "\tgrad: tensor([-0.1257,  0.7115])\n",
      "\tparams: tensor([  4.6291, -13.1236])\n",
      "Epoch: 844,Loss: 4.458913\n",
      "\tgrad: tensor([-0.1255,  0.7103])\n",
      "\tparams: tensor([  4.6304, -13.1307])\n",
      "Epoch: 845,Loss: 4.453716\n",
      "\tgrad: tensor([-0.1253,  0.7091])\n",
      "\tparams: tensor([  4.6316, -13.1378])\n",
      "Epoch: 846,Loss: 4.448535\n",
      "\tgrad: tensor([-0.1250,  0.7079])\n",
      "\tparams: tensor([  4.6329, -13.1449])\n",
      "Epoch: 847,Loss: 4.443372\n",
      "\tgrad: tensor([-0.1249,  0.7067])\n",
      "\tparams: tensor([  4.6341, -13.1519])\n",
      "Epoch: 848,Loss: 4.438226\n",
      "\tgrad: tensor([-0.1246,  0.7055])\n",
      "\tparams: tensor([  4.6353, -13.1590])\n",
      "Epoch: 849,Loss: 4.433099\n",
      "\tgrad: tensor([-0.1244,  0.7043])\n",
      "\tparams: tensor([  4.6366, -13.1660])\n",
      "Epoch: 850,Loss: 4.427990\n",
      "\tgrad: tensor([-0.1242,  0.7031])\n",
      "\tparams: tensor([  4.6378, -13.1730])\n",
      "Epoch: 851,Loss: 4.422897\n",
      "\tgrad: tensor([-0.1240,  0.7019])\n",
      "\tparams: tensor([  4.6391, -13.1801])\n",
      "Epoch: 852,Loss: 4.417819\n",
      "\tgrad: tensor([-0.1238,  0.7007])\n",
      "\tparams: tensor([  4.6403, -13.1871])\n",
      "Epoch: 853,Loss: 4.412762\n",
      "\tgrad: tensor([-0.1236,  0.6995])\n",
      "\tparams: tensor([  4.6415, -13.1941])\n",
      "Epoch: 854,Loss: 4.407721\n",
      "\tgrad: tensor([-0.1234,  0.6983])\n",
      "\tparams: tensor([  4.6428, -13.2010])\n",
      "Epoch: 855,Loss: 4.402698\n",
      "\tgrad: tensor([-0.1232,  0.6971])\n",
      "\tparams: tensor([  4.6440, -13.2080])\n",
      "Epoch: 856,Loss: 4.397688\n",
      "\tgrad: tensor([-0.1229,  0.6959])\n",
      "\tparams: tensor([  4.6452, -13.2150])\n",
      "Epoch: 857,Loss: 4.392697\n",
      "\tgrad: tensor([-0.1227,  0.6948])\n",
      "\tparams: tensor([  4.6465, -13.2219])\n",
      "Epoch: 858,Loss: 4.387725\n",
      "\tgrad: tensor([-0.1225,  0.6936])\n",
      "\tparams: tensor([  4.6477, -13.2289])\n",
      "Epoch: 859,Loss: 4.382770\n",
      "\tgrad: tensor([-0.1223,  0.6924])\n",
      "\tparams: tensor([  4.6489, -13.2358])\n",
      "Epoch: 860,Loss: 4.377828\n",
      "\tgrad: tensor([-0.1221,  0.6912])\n",
      "\tparams: tensor([  4.6501, -13.2427])\n",
      "Epoch: 861,Loss: 4.372905\n",
      "\tgrad: tensor([-0.1219,  0.6901])\n",
      "\tparams: tensor([  4.6514, -13.2496])\n",
      "Epoch: 862,Loss: 4.368000\n",
      "\tgrad: tensor([-0.1217,  0.6889])\n",
      "\tparams: tensor([  4.6526, -13.2565])\n",
      "Epoch: 863,Loss: 4.363111\n",
      "\tgrad: tensor([-0.1215,  0.6877])\n",
      "\tparams: tensor([  4.6538, -13.2634])\n",
      "Epoch: 864,Loss: 4.358238\n",
      "\tgrad: tensor([-0.1213,  0.6865])\n",
      "\tparams: tensor([  4.6550, -13.2702])\n",
      "Epoch: 865,Loss: 4.353383\n",
      "\tgrad: tensor([-0.1211,  0.6854])\n",
      "\tparams: tensor([  4.6562, -13.2771])\n",
      "Epoch: 866,Loss: 4.348542\n",
      "\tgrad: tensor([-0.1209,  0.6842])\n",
      "\tparams: tensor([  4.6574, -13.2839])\n",
      "Epoch: 867,Loss: 4.343716\n",
      "\tgrad: tensor([-0.1207,  0.6830])\n",
      "\tparams: tensor([  4.6586, -13.2908])\n",
      "Epoch: 868,Loss: 4.338911\n",
      "\tgrad: tensor([-0.1205,  0.6819])\n",
      "\tparams: tensor([  4.6598, -13.2976])\n",
      "Epoch: 869,Loss: 4.334120\n",
      "\tgrad: tensor([-0.1203,  0.6807])\n",
      "\tparams: tensor([  4.6610, -13.3044])\n",
      "Epoch: 870,Loss: 4.329345\n",
      "\tgrad: tensor([-0.1201,  0.6796])\n",
      "\tparams: tensor([  4.6622, -13.3112])\n",
      "Epoch: 871,Loss: 4.324588\n",
      "\tgrad: tensor([-0.1198,  0.6784])\n",
      "\tparams: tensor([  4.6634, -13.3180])\n",
      "Epoch: 872,Loss: 4.319846\n",
      "\tgrad: tensor([-0.1196,  0.6773])\n",
      "\tparams: tensor([  4.6646, -13.3247])\n",
      "Epoch: 873,Loss: 4.315117\n",
      "\tgrad: tensor([-0.1195,  0.6761])\n",
      "\tparams: tensor([  4.6658, -13.3315])\n",
      "Epoch: 874,Loss: 4.310409\n",
      "\tgrad: tensor([-0.1192,  0.6750])\n",
      "\tparams: tensor([  4.6670, -13.3382])\n",
      "Epoch: 875,Loss: 4.305714\n",
      "\tgrad: tensor([-0.1190,  0.6738])\n",
      "\tparams: tensor([  4.6682, -13.3450])\n",
      "Epoch: 876,Loss: 4.301036\n",
      "\tgrad: tensor([-0.1188,  0.6727])\n",
      "\tparams: tensor([  4.6694, -13.3517])\n",
      "Epoch: 877,Loss: 4.296376\n",
      "\tgrad: tensor([-0.1186,  0.6715])\n",
      "\tparams: tensor([  4.6706, -13.3584])\n",
      "Epoch: 878,Loss: 4.291727\n",
      "\tgrad: tensor([-0.1184,  0.6704])\n",
      "\tparams: tensor([  4.6718, -13.3651])\n",
      "Epoch: 879,Loss: 4.287098\n",
      "\tgrad: tensor([-0.1182,  0.6693])\n",
      "\tparams: tensor([  4.6730, -13.3718])\n",
      "Epoch: 880,Loss: 4.282482\n",
      "\tgrad: tensor([-0.1180,  0.6681])\n",
      "\tparams: tensor([  4.6741, -13.3785])\n",
      "Epoch: 881,Loss: 4.277882\n",
      "\tgrad: tensor([-0.1178,  0.6670])\n",
      "\tparams: tensor([  4.6753, -13.3852])\n",
      "Epoch: 882,Loss: 4.273299\n",
      "\tgrad: tensor([-0.1176,  0.6658])\n",
      "\tparams: tensor([  4.6765, -13.3918])\n",
      "Epoch: 883,Loss: 4.268732\n",
      "\tgrad: tensor([-0.1174,  0.6647])\n",
      "\tparams: tensor([  4.6777, -13.3985])\n",
      "Epoch: 884,Loss: 4.264178\n",
      "\tgrad: tensor([-0.1172,  0.6636])\n",
      "\tparams: tensor([  4.6788, -13.4051])\n",
      "Epoch: 885,Loss: 4.259643\n",
      "\tgrad: tensor([-0.1170,  0.6625])\n",
      "\tparams: tensor([  4.6800, -13.4117])\n",
      "Epoch: 886,Loss: 4.255120\n",
      "\tgrad: tensor([-0.1168,  0.6613])\n",
      "\tparams: tensor([  4.6812, -13.4184])\n",
      "Epoch: 887,Loss: 4.250614\n",
      "\tgrad: tensor([-0.1166,  0.6602])\n",
      "\tparams: tensor([  4.6823, -13.4250])\n",
      "Epoch: 888,Loss: 4.246124\n",
      "\tgrad: tensor([-0.1164,  0.6591])\n",
      "\tparams: tensor([  4.6835, -13.4316])\n",
      "Epoch: 889,Loss: 4.241648\n",
      "\tgrad: tensor([-0.1162,  0.6580])\n",
      "\tparams: tensor([  4.6847, -13.4381])\n",
      "Epoch: 890,Loss: 4.237185\n",
      "\tgrad: tensor([-0.1160,  0.6569])\n",
      "\tparams: tensor([  4.6858, -13.4447])\n",
      "Epoch: 891,Loss: 4.232740\n",
      "\tgrad: tensor([-0.1158,  0.6557])\n",
      "\tparams: tensor([  4.6870, -13.4513])\n",
      "Epoch: 892,Loss: 4.228308\n",
      "\tgrad: tensor([-0.1157,  0.6546])\n",
      "\tparams: tensor([  4.6881, -13.4578])\n",
      "Epoch: 893,Loss: 4.223895\n",
      "\tgrad: tensor([-0.1154,  0.6535])\n",
      "\tparams: tensor([  4.6893, -13.4643])\n",
      "Epoch: 894,Loss: 4.219494\n",
      "\tgrad: tensor([-0.1153,  0.6524])\n",
      "\tparams: tensor([  4.6904, -13.4709])\n",
      "Epoch: 895,Loss: 4.215109\n",
      "\tgrad: tensor([-0.1151,  0.6513])\n",
      "\tparams: tensor([  4.6916, -13.4774])\n",
      "Epoch: 896,Loss: 4.210737\n",
      "\tgrad: tensor([-0.1148,  0.6502])\n",
      "\tparams: tensor([  4.6927, -13.4839])\n",
      "Epoch: 897,Loss: 4.206383\n",
      "\tgrad: tensor([-0.1147,  0.6491])\n",
      "\tparams: tensor([  4.6939, -13.4904])\n",
      "Epoch: 898,Loss: 4.202043\n",
      "\tgrad: tensor([-0.1145,  0.6480])\n",
      "\tparams: tensor([  4.6950, -13.4968])\n",
      "Epoch: 899,Loss: 4.197715\n",
      "\tgrad: tensor([-0.1143,  0.6469])\n",
      "\tparams: tensor([  4.6962, -13.5033])\n",
      "Epoch: 900,Loss: 4.193405\n",
      "\tgrad: tensor([-0.1141,  0.6458])\n",
      "\tparams: tensor([  4.6973, -13.5098])\n",
      "Epoch: 901,Loss: 4.189108\n",
      "\tgrad: tensor([-0.1139,  0.6447])\n",
      "\tparams: tensor([  4.6985, -13.5162])\n",
      "Epoch: 902,Loss: 4.184825\n",
      "\tgrad: tensor([-0.1137,  0.6436])\n",
      "\tparams: tensor([  4.6996, -13.5227])\n",
      "Epoch: 903,Loss: 4.180559\n",
      "\tgrad: tensor([-0.1135,  0.6425])\n",
      "\tparams: tensor([  4.7007, -13.5291])\n",
      "Epoch: 904,Loss: 4.176305\n",
      "\tgrad: tensor([-0.1133,  0.6414])\n",
      "\tparams: tensor([  4.7019, -13.5355])\n",
      "Epoch: 905,Loss: 4.172065\n",
      "\tgrad: tensor([-0.1131,  0.6403])\n",
      "\tparams: tensor([  4.7030, -13.5419])\n",
      "Epoch: 906,Loss: 4.167842\n",
      "\tgrad: tensor([-0.1129,  0.6392])\n",
      "\tparams: tensor([  4.7041, -13.5483])\n",
      "Epoch: 907,Loss: 4.163630\n",
      "\tgrad: tensor([-0.1127,  0.6381])\n",
      "\tparams: tensor([  4.7053, -13.5547])\n",
      "Epoch: 908,Loss: 4.159436\n",
      "\tgrad: tensor([-0.1125,  0.6371])\n",
      "\tparams: tensor([  4.7064, -13.5610])\n",
      "Epoch: 909,Loss: 4.155253\n",
      "\tgrad: tensor([-0.1124,  0.6360])\n",
      "\tparams: tensor([  4.7075, -13.5674])\n",
      "Epoch: 910,Loss: 4.151086\n",
      "\tgrad: tensor([-0.1122,  0.6349])\n",
      "\tparams: tensor([  4.7086, -13.5738])\n",
      "Epoch: 911,Loss: 4.146934\n",
      "\tgrad: tensor([-0.1120,  0.6338])\n",
      "\tparams: tensor([  4.7097, -13.5801])\n",
      "Epoch: 912,Loss: 4.142794\n",
      "\tgrad: tensor([-0.1118,  0.6327])\n",
      "\tparams: tensor([  4.7109, -13.5864])\n",
      "Epoch: 913,Loss: 4.138669\n",
      "\tgrad: tensor([-0.1116,  0.6317])\n",
      "\tparams: tensor([  4.7120, -13.5927])\n",
      "Epoch: 914,Loss: 4.134559\n",
      "\tgrad: tensor([-0.1114,  0.6306])\n",
      "\tparams: tensor([  4.7131, -13.5990])\n",
      "Epoch: 915,Loss: 4.130465\n",
      "\tgrad: tensor([-0.1112,  0.6295])\n",
      "\tparams: tensor([  4.7142, -13.6053])\n",
      "Epoch: 916,Loss: 4.126378\n",
      "\tgrad: tensor([-0.1110,  0.6284])\n",
      "\tparams: tensor([  4.7153, -13.6116])\n",
      "Epoch: 917,Loss: 4.122310\n",
      "\tgrad: tensor([-0.1108,  0.6274])\n",
      "\tparams: tensor([  4.7164, -13.6179])\n",
      "Epoch: 918,Loss: 4.118253\n",
      "\tgrad: tensor([-0.1107,  0.6263])\n",
      "\tparams: tensor([  4.7175, -13.6242])\n",
      "Epoch: 919,Loss: 4.114213\n",
      "\tgrad: tensor([-0.1104,  0.6253])\n",
      "\tparams: tensor([  4.7186, -13.6304])\n",
      "Epoch: 920,Loss: 4.110184\n",
      "\tgrad: tensor([-0.1103,  0.6242])\n",
      "\tparams: tensor([  4.7197, -13.6367])\n",
      "Epoch: 921,Loss: 4.106170\n",
      "\tgrad: tensor([-0.1101,  0.6231])\n",
      "\tparams: tensor([  4.7208, -13.6429])\n",
      "Epoch: 922,Loss: 4.102171\n",
      "\tgrad: tensor([-0.1099,  0.6221])\n",
      "\tparams: tensor([  4.7219, -13.6491])\n",
      "Epoch: 923,Loss: 4.098181\n",
      "\tgrad: tensor([-0.1097,  0.6210])\n",
      "\tparams: tensor([  4.7230, -13.6553])\n",
      "Epoch: 924,Loss: 4.094209\n",
      "\tgrad: tensor([-0.1095,  0.6200])\n",
      "\tparams: tensor([  4.7241, -13.6615])\n",
      "Epoch: 925,Loss: 4.090250\n",
      "\tgrad: tensor([-0.1093,  0.6189])\n",
      "\tparams: tensor([  4.7252, -13.6677])\n",
      "Epoch: 926,Loss: 4.086300\n",
      "\tgrad: tensor([-0.1091,  0.6179])\n",
      "\tparams: tensor([  4.7263, -13.6739])\n",
      "Epoch: 927,Loss: 4.082366\n",
      "\tgrad: tensor([-0.1090,  0.6168])\n",
      "\tparams: tensor([  4.7274, -13.6800])\n",
      "Epoch: 928,Loss: 4.078448\n",
      "\tgrad: tensor([-0.1088,  0.6158])\n",
      "\tparams: tensor([  4.7285, -13.6862])\n",
      "Epoch: 929,Loss: 4.074540\n",
      "\tgrad: tensor([-0.1086,  0.6147])\n",
      "\tparams: tensor([  4.7296, -13.6924])\n",
      "Epoch: 930,Loss: 4.070650\n",
      "\tgrad: tensor([-0.1084,  0.6137])\n",
      "\tparams: tensor([  4.7307, -13.6985])\n",
      "Epoch: 931,Loss: 4.066769\n",
      "\tgrad: tensor([-0.1082,  0.6126])\n",
      "\tparams: tensor([  4.7317, -13.7046])\n",
      "Epoch: 932,Loss: 4.062900\n",
      "\tgrad: tensor([-0.1080,  0.6116])\n",
      "\tparams: tensor([  4.7328, -13.7107])\n",
      "Epoch: 933,Loss: 4.059047\n",
      "\tgrad: tensor([-0.1079,  0.6105])\n",
      "\tparams: tensor([  4.7339, -13.7168])\n",
      "Epoch: 934,Loss: 4.055204\n",
      "\tgrad: tensor([-0.1077,  0.6095])\n",
      "\tparams: tensor([  4.7350, -13.7229])\n",
      "Epoch: 935,Loss: 4.051378\n",
      "\tgrad: tensor([-0.1075,  0.6085])\n",
      "\tparams: tensor([  4.7360, -13.7290])\n",
      "Epoch: 936,Loss: 4.047564\n",
      "\tgrad: tensor([-0.1073,  0.6074])\n",
      "\tparams: tensor([  4.7371, -13.7351])\n",
      "Epoch: 937,Loss: 4.043762\n",
      "\tgrad: tensor([-0.1071,  0.6064])\n",
      "\tparams: tensor([  4.7382, -13.7412])\n",
      "Epoch: 938,Loss: 4.039972\n",
      "\tgrad: tensor([-0.1069,  0.6054])\n",
      "\tparams: tensor([  4.7393, -13.7472])\n",
      "Epoch: 939,Loss: 4.036197\n",
      "\tgrad: tensor([-0.1068,  0.6043])\n",
      "\tparams: tensor([  4.7403, -13.7533])\n",
      "Epoch: 940,Loss: 4.032433\n",
      "\tgrad: tensor([-0.1066,  0.6033])\n",
      "\tparams: tensor([  4.7414, -13.7593])\n",
      "Epoch: 941,Loss: 4.028685\n",
      "\tgrad: tensor([-0.1064,  0.6023])\n",
      "\tparams: tensor([  4.7425, -13.7653])\n",
      "Epoch: 942,Loss: 4.024947\n",
      "\tgrad: tensor([-0.1062,  0.6013])\n",
      "\tparams: tensor([  4.7435, -13.7713])\n",
      "Epoch: 943,Loss: 4.021221\n",
      "\tgrad: tensor([-0.1060,  0.6003])\n",
      "\tparams: tensor([  4.7446, -13.7773])\n",
      "Epoch: 944,Loss: 4.017508\n",
      "\tgrad: tensor([-0.1058,  0.5992])\n",
      "\tparams: tensor([  4.7456, -13.7833])\n",
      "Epoch: 945,Loss: 4.013809\n",
      "\tgrad: tensor([-0.1057,  0.5982])\n",
      "\tparams: tensor([  4.7467, -13.7893])\n",
      "Epoch: 946,Loss: 4.010123\n",
      "\tgrad: tensor([-0.1055,  0.5972])\n",
      "\tparams: tensor([  4.7478, -13.7953])\n",
      "Epoch: 947,Loss: 4.006446\n",
      "\tgrad: tensor([-0.1053,  0.5962])\n",
      "\tparams: tensor([  4.7488, -13.8012])\n",
      "Epoch: 948,Loss: 4.002786\n",
      "\tgrad: tensor([-0.1051,  0.5952])\n",
      "\tparams: tensor([  4.7499, -13.8072])\n",
      "Epoch: 949,Loss: 3.999135\n",
      "\tgrad: tensor([-0.1050,  0.5942])\n",
      "\tparams: tensor([  4.7509, -13.8131])\n",
      "Epoch: 950,Loss: 3.995498\n",
      "\tgrad: tensor([-0.1048,  0.5931])\n",
      "\tparams: tensor([  4.7520, -13.8191])\n",
      "Epoch: 951,Loss: 3.991874\n",
      "\tgrad: tensor([-0.1046,  0.5921])\n",
      "\tparams: tensor([  4.7530, -13.8250])\n",
      "Epoch: 952,Loss: 3.988261\n",
      "\tgrad: tensor([-0.1044,  0.5911])\n",
      "\tparams: tensor([  4.7540, -13.8309])\n",
      "Epoch: 953,Loss: 3.984660\n",
      "\tgrad: tensor([-0.1042,  0.5901])\n",
      "\tparams: tensor([  4.7551, -13.8368])\n",
      "Epoch: 954,Loss: 3.981073\n",
      "\tgrad: tensor([-0.1041,  0.5891])\n",
      "\tparams: tensor([  4.7561, -13.8427])\n",
      "Epoch: 955,Loss: 3.977496\n",
      "\tgrad: tensor([-0.1039,  0.5881])\n",
      "\tparams: tensor([  4.7572, -13.8486])\n",
      "Epoch: 956,Loss: 3.973931\n",
      "\tgrad: tensor([-0.1037,  0.5871])\n",
      "\tparams: tensor([  4.7582, -13.8544])\n",
      "Epoch: 957,Loss: 3.970381\n",
      "\tgrad: tensor([-0.1035,  0.5861])\n",
      "\tparams: tensor([  4.7592, -13.8603])\n",
      "Epoch: 958,Loss: 3.966841\n",
      "\tgrad: tensor([-0.1034,  0.5851])\n",
      "\tparams: tensor([  4.7603, -13.8661])\n",
      "Epoch: 959,Loss: 3.963313\n",
      "\tgrad: tensor([-0.1032,  0.5841])\n",
      "\tparams: tensor([  4.7613, -13.8720])\n",
      "Epoch: 960,Loss: 3.959796\n",
      "\tgrad: tensor([-0.1030,  0.5831])\n",
      "\tparams: tensor([  4.7623, -13.8778])\n",
      "Epoch: 961,Loss: 3.956295\n",
      "\tgrad: tensor([-0.1028,  0.5822])\n",
      "\tparams: tensor([  4.7634, -13.8836])\n",
      "Epoch: 962,Loss: 3.952801\n",
      "\tgrad: tensor([-0.1026,  0.5812])\n",
      "\tparams: tensor([  4.7644, -13.8895])\n",
      "Epoch: 963,Loss: 3.949323\n",
      "\tgrad: tensor([-0.1025,  0.5802])\n",
      "\tparams: tensor([  4.7654, -13.8953])\n",
      "Epoch: 964,Loss: 3.945855\n",
      "\tgrad: tensor([-0.1023,  0.5792])\n",
      "\tparams: tensor([  4.7664, -13.9010])\n",
      "Epoch: 965,Loss: 3.942398\n",
      "\tgrad: tensor([-0.1021,  0.5782])\n",
      "\tparams: tensor([  4.7675, -13.9068])\n",
      "Epoch: 966,Loss: 3.938954\n",
      "\tgrad: tensor([-0.1020,  0.5772])\n",
      "\tparams: tensor([  4.7685, -13.9126])\n",
      "Epoch: 967,Loss: 3.935520\n",
      "\tgrad: tensor([-0.1018,  0.5762])\n",
      "\tparams: tensor([  4.7695, -13.9184])\n",
      "Epoch: 968,Loss: 3.932096\n",
      "\tgrad: tensor([-0.1016,  0.5753])\n",
      "\tparams: tensor([  4.7705, -13.9241])\n",
      "Epoch: 969,Loss: 3.928688\n",
      "\tgrad: tensor([-0.1015,  0.5743])\n",
      "\tparams: tensor([  4.7715, -13.9299])\n",
      "Epoch: 970,Loss: 3.925292\n",
      "\tgrad: tensor([-0.1013,  0.5733])\n",
      "\tparams: tensor([  4.7725, -13.9356])\n",
      "Epoch: 971,Loss: 3.921906\n",
      "\tgrad: tensor([-0.1011,  0.5723])\n",
      "\tparams: tensor([  4.7736, -13.9413])\n",
      "Epoch: 972,Loss: 3.918527\n",
      "\tgrad: tensor([-0.1009,  0.5714])\n",
      "\tparams: tensor([  4.7746, -13.9470])\n",
      "Epoch: 973,Loss: 3.915166\n",
      "\tgrad: tensor([-0.1008,  0.5704])\n",
      "\tparams: tensor([  4.7756, -13.9527])\n",
      "Epoch: 974,Loss: 3.911815\n",
      "\tgrad: tensor([-0.1006,  0.5694])\n",
      "\tparams: tensor([  4.7766, -13.9584])\n",
      "Epoch: 975,Loss: 3.908474\n",
      "\tgrad: tensor([-0.1004,  0.5685])\n",
      "\tparams: tensor([  4.7776, -13.9641])\n",
      "Epoch: 976,Loss: 3.905143\n",
      "\tgrad: tensor([-0.1003,  0.5675])\n",
      "\tparams: tensor([  4.7786, -13.9698])\n",
      "Epoch: 977,Loss: 3.901825\n",
      "\tgrad: tensor([-0.1001,  0.5665])\n",
      "\tparams: tensor([  4.7796, -13.9755])\n",
      "Epoch: 978,Loss: 3.898517\n",
      "\tgrad: tensor([-0.0999,  0.5656])\n",
      "\tparams: tensor([  4.7806, -13.9811])\n",
      "Epoch: 979,Loss: 3.895222\n",
      "\tgrad: tensor([-0.0997,  0.5646])\n",
      "\tparams: tensor([  4.7816, -13.9868])\n",
      "Epoch: 980,Loss: 3.891935\n",
      "\tgrad: tensor([-0.0996,  0.5637])\n",
      "\tparams: tensor([  4.7826, -13.9924])\n",
      "Epoch: 981,Loss: 3.888664\n",
      "\tgrad: tensor([-0.0994,  0.5627])\n",
      "\tparams: tensor([  4.7836, -13.9980])\n",
      "Epoch: 982,Loss: 3.885401\n",
      "\tgrad: tensor([-0.0992,  0.5617])\n",
      "\tparams: tensor([  4.7846, -14.0036])\n",
      "Epoch: 983,Loss: 3.882150\n",
      "\tgrad: tensor([-0.0991,  0.5608])\n",
      "\tparams: tensor([  4.7856, -14.0092])\n",
      "Epoch: 984,Loss: 3.878910\n",
      "\tgrad: tensor([-0.0989,  0.5598])\n",
      "\tparams: tensor([  4.7865, -14.0148])\n",
      "Epoch: 985,Loss: 3.875680\n",
      "\tgrad: tensor([-0.0987,  0.5589])\n",
      "\tparams: tensor([  4.7875, -14.0204])\n",
      "Epoch: 986,Loss: 3.872463\n",
      "\tgrad: tensor([-0.0986,  0.5579])\n",
      "\tparams: tensor([  4.7885, -14.0260])\n",
      "Epoch: 987,Loss: 3.869256\n",
      "\tgrad: tensor([-0.0984,  0.5570])\n",
      "\tparams: tensor([  4.7895, -14.0316])\n",
      "Epoch: 988,Loss: 3.866060\n",
      "\tgrad: tensor([-0.0982,  0.5560])\n",
      "\tparams: tensor([  4.7905, -14.0371])\n",
      "Epoch: 989,Loss: 3.862872\n",
      "\tgrad: tensor([-0.0981,  0.5551])\n",
      "\tparams: tensor([  4.7915, -14.0427])\n",
      "Epoch: 990,Loss: 3.859699\n",
      "\tgrad: tensor([-0.0979,  0.5541])\n",
      "\tparams: tensor([  4.7924, -14.0482])\n",
      "Epoch: 991,Loss: 3.856535\n",
      "\tgrad: tensor([-0.0978,  0.5532])\n",
      "\tparams: tensor([  4.7934, -14.0538])\n",
      "Epoch: 992,Loss: 3.853381\n",
      "\tgrad: tensor([-0.0976,  0.5523])\n",
      "\tparams: tensor([  4.7944, -14.0593])\n",
      "Epoch: 993,Loss: 3.850237\n",
      "\tgrad: tensor([-0.0974,  0.5513])\n",
      "\tparams: tensor([  4.7954, -14.0648])\n",
      "Epoch: 994,Loss: 3.847109\n",
      "\tgrad: tensor([-0.0973,  0.5504])\n",
      "\tparams: tensor([  4.7963, -14.0703])\n",
      "Epoch: 995,Loss: 3.843984\n",
      "\tgrad: tensor([-0.0971,  0.5495])\n",
      "\tparams: tensor([  4.7973, -14.0758])\n",
      "Epoch: 996,Loss: 3.840876\n",
      "\tgrad: tensor([-0.0969,  0.5485])\n",
      "\tparams: tensor([  4.7983, -14.0813])\n",
      "Epoch: 997,Loss: 3.837775\n",
      "\tgrad: tensor([-0.0967,  0.5476])\n",
      "\tparams: tensor([  4.7992, -14.0868])\n",
      "Epoch: 998,Loss: 3.834686\n",
      "\tgrad: tensor([-0.0966,  0.5467])\n",
      "\tparams: tensor([  4.8002, -14.0922])\n",
      "Epoch: 999,Loss: 3.831606\n",
      "\tgrad: tensor([-0.0964,  0.5457])\n",
      "\tparams: tensor([  4.8012, -14.0977])\n",
      "Epoch: 1000,Loss: 3.828538\n",
      "\tgrad: tensor([-0.0962,  0.5448])\n",
      "\tparams: tensor([  4.8021, -14.1031])\n",
      "Epoch: 1001,Loss: 3.825483\n",
      "\tgrad: tensor([-0.0961,  0.5439])\n",
      "\tparams: tensor([  4.8031, -14.1086])\n",
      "Epoch: 1002,Loss: 3.822433\n",
      "\tgrad: tensor([-0.0959,  0.5430])\n",
      "\tparams: tensor([  4.8041, -14.1140])\n",
      "Epoch: 1003,Loss: 3.819398\n",
      "\tgrad: tensor([-0.0957,  0.5420])\n",
      "\tparams: tensor([  4.8050, -14.1194])\n",
      "Epoch: 1004,Loss: 3.816369\n",
      "\tgrad: tensor([-0.0956,  0.5411])\n",
      "\tparams: tensor([  4.8060, -14.1248])\n",
      "Epoch: 1005,Loss: 3.813350\n",
      "\tgrad: tensor([-0.0954,  0.5402])\n",
      "\tparams: tensor([  4.8069, -14.1302])\n",
      "Epoch: 1006,Loss: 3.810344\n",
      "\tgrad: tensor([-0.0953,  0.5393])\n",
      "\tparams: tensor([  4.8079, -14.1356])\n",
      "Epoch: 1007,Loss: 3.807348\n",
      "\tgrad: tensor([-0.0951,  0.5384])\n",
      "\tparams: tensor([  4.8088, -14.1410])\n",
      "Epoch: 1008,Loss: 3.804360\n",
      "\tgrad: tensor([-0.0949,  0.5375])\n",
      "\tparams: tensor([  4.8098, -14.1464])\n",
      "Epoch: 1009,Loss: 3.801384\n",
      "\tgrad: tensor([-0.0948,  0.5365])\n",
      "\tparams: tensor([  4.8107, -14.1518])\n",
      "Epoch: 1010,Loss: 3.798421\n",
      "\tgrad: tensor([-0.0946,  0.5356])\n",
      "\tparams: tensor([  4.8117, -14.1571])\n",
      "Epoch: 1011,Loss: 3.795465\n",
      "\tgrad: tensor([-0.0945,  0.5347])\n",
      "\tparams: tensor([  4.8126, -14.1625])\n",
      "Epoch: 1012,Loss: 3.792518\n",
      "\tgrad: tensor([-0.0943,  0.5338])\n",
      "\tparams: tensor([  4.8136, -14.1678])\n",
      "Epoch: 1013,Loss: 3.789584\n",
      "\tgrad: tensor([-0.0942,  0.5329])\n",
      "\tparams: tensor([  4.8145, -14.1731])\n",
      "Epoch: 1014,Loss: 3.786658\n",
      "\tgrad: tensor([-0.0940,  0.5320])\n",
      "\tparams: tensor([  4.8154, -14.1784])\n",
      "Epoch: 1015,Loss: 3.783740\n",
      "\tgrad: tensor([-0.0938,  0.5311])\n",
      "\tparams: tensor([  4.8164, -14.1838])\n",
      "Epoch: 1016,Loss: 3.780832\n",
      "\tgrad: tensor([-0.0937,  0.5302])\n",
      "\tparams: tensor([  4.8173, -14.1891])\n",
      "Epoch: 1017,Loss: 3.777939\n",
      "\tgrad: tensor([-0.0935,  0.5293])\n",
      "\tparams: tensor([  4.8183, -14.1943])\n",
      "Epoch: 1018,Loss: 3.775053\n",
      "\tgrad: tensor([-0.0933,  0.5284])\n",
      "\tparams: tensor([  4.8192, -14.1996])\n",
      "Epoch: 1019,Loss: 3.772173\n",
      "\tgrad: tensor([-0.0932,  0.5275])\n",
      "\tparams: tensor([  4.8201, -14.2049])\n",
      "Epoch: 1020,Loss: 3.769311\n",
      "\tgrad: tensor([-0.0930,  0.5266])\n",
      "\tparams: tensor([  4.8210, -14.2102])\n",
      "Epoch: 1021,Loss: 3.766450\n",
      "\tgrad: tensor([-0.0929,  0.5257])\n",
      "\tparams: tensor([  4.8220, -14.2154])\n",
      "Epoch: 1022,Loss: 3.763602\n",
      "\tgrad: tensor([-0.0927,  0.5248])\n",
      "\tparams: tensor([  4.8229, -14.2207])\n",
      "Epoch: 1023,Loss: 3.760766\n",
      "\tgrad: tensor([-0.0926,  0.5239])\n",
      "\tparams: tensor([  4.8238, -14.2259])\n",
      "Epoch: 1024,Loss: 3.757936\n",
      "\tgrad: tensor([-0.0924,  0.5230])\n",
      "\tparams: tensor([  4.8248, -14.2311])\n",
      "Epoch: 1025,Loss: 3.755118\n",
      "\tgrad: tensor([-0.0922,  0.5221])\n",
      "\tparams: tensor([  4.8257, -14.2364])\n",
      "Epoch: 1026,Loss: 3.752309\n",
      "\tgrad: tensor([-0.0921,  0.5213])\n",
      "\tparams: tensor([  4.8266, -14.2416])\n",
      "Epoch: 1027,Loss: 3.749511\n",
      "\tgrad: tensor([-0.0919,  0.5204])\n",
      "\tparams: tensor([  4.8275, -14.2468])\n",
      "Epoch: 1028,Loss: 3.746722\n",
      "\tgrad: tensor([-0.0918,  0.5195])\n",
      "\tparams: tensor([  4.8284, -14.2520])\n",
      "Epoch: 1029,Loss: 3.743940\n",
      "\tgrad: tensor([-0.0916,  0.5186])\n",
      "\tparams: tensor([  4.8293, -14.2572])\n",
      "Epoch: 1030,Loss: 3.741169\n",
      "\tgrad: tensor([-0.0915,  0.5177])\n",
      "\tparams: tensor([  4.8303, -14.2623])\n",
      "Epoch: 1031,Loss: 3.738407\n",
      "\tgrad: tensor([-0.0913,  0.5168])\n",
      "\tparams: tensor([  4.8312, -14.2675])\n",
      "Epoch: 1032,Loss: 3.735656\n",
      "\tgrad: tensor([-0.0912,  0.5160])\n",
      "\tparams: tensor([  4.8321, -14.2727])\n",
      "Epoch: 1033,Loss: 3.732914\n",
      "\tgrad: tensor([-0.0910,  0.5151])\n",
      "\tparams: tensor([  4.8330, -14.2778])\n",
      "Epoch: 1034,Loss: 3.730181\n",
      "\tgrad: tensor([-0.0908,  0.5142])\n",
      "\tparams: tensor([  4.8339, -14.2830])\n",
      "Epoch: 1035,Loss: 3.727456\n",
      "\tgrad: tensor([-0.0907,  0.5133])\n",
      "\tparams: tensor([  4.8348, -14.2881])\n",
      "Epoch: 1036,Loss: 3.724740\n",
      "\tgrad: tensor([-0.0905,  0.5125])\n",
      "\tparams: tensor([  4.8357, -14.2932])\n",
      "Epoch: 1037,Loss: 3.722034\n",
      "\tgrad: tensor([-0.0904,  0.5116])\n",
      "\tparams: tensor([  4.8366, -14.2983])\n",
      "Epoch: 1038,Loss: 3.719337\n",
      "\tgrad: tensor([-0.0902,  0.5107])\n",
      "\tparams: tensor([  4.8375, -14.3034])\n",
      "Epoch: 1039,Loss: 3.716651\n",
      "\tgrad: tensor([-0.0901,  0.5099])\n",
      "\tparams: tensor([  4.8384, -14.3085])\n",
      "Epoch: 1040,Loss: 3.713972\n",
      "\tgrad: tensor([-0.0899,  0.5090])\n",
      "\tparams: tensor([  4.8393, -14.3136])\n",
      "Epoch: 1041,Loss: 3.711302\n",
      "\tgrad: tensor([-0.0898,  0.5081])\n",
      "\tparams: tensor([  4.8402, -14.3187])\n",
      "Epoch: 1042,Loss: 3.708644\n",
      "\tgrad: tensor([-0.0896,  0.5073])\n",
      "\tparams: tensor([  4.8411, -14.3238])\n",
      "Epoch: 1043,Loss: 3.705991\n",
      "\tgrad: tensor([-0.0895,  0.5064])\n",
      "\tparams: tensor([  4.8420, -14.3288])\n",
      "Epoch: 1044,Loss: 3.703351\n",
      "\tgrad: tensor([-0.0893,  0.5055])\n",
      "\tparams: tensor([  4.8429, -14.3339])\n",
      "Epoch: 1045,Loss: 3.700716\n",
      "\tgrad: tensor([-0.0892,  0.5047])\n",
      "\tparams: tensor([  4.8438, -14.3390])\n",
      "Epoch: 1046,Loss: 3.698091\n",
      "\tgrad: tensor([-0.0890,  0.5038])\n",
      "\tparams: tensor([  4.8447, -14.3440])\n",
      "Epoch: 1047,Loss: 3.695476\n",
      "\tgrad: tensor([-0.0888,  0.5030])\n",
      "\tparams: tensor([  4.8456, -14.3490])\n",
      "Epoch: 1048,Loss: 3.692869\n",
      "\tgrad: tensor([-0.0887,  0.5021])\n",
      "\tparams: tensor([  4.8465, -14.3540])\n",
      "Epoch: 1049,Loss: 3.690273\n",
      "\tgrad: tensor([-0.0886,  0.5013])\n",
      "\tparams: tensor([  4.8473, -14.3591])\n",
      "Epoch: 1050,Loss: 3.687683\n",
      "\tgrad: tensor([-0.0884,  0.5004])\n",
      "\tparams: tensor([  4.8482, -14.3641])\n",
      "Epoch: 1051,Loss: 3.685104\n",
      "\tgrad: tensor([-0.0882,  0.4996])\n",
      "\tparams: tensor([  4.8491, -14.3691])\n",
      "Epoch: 1052,Loss: 3.682532\n",
      "\tgrad: tensor([-0.0881,  0.4987])\n",
      "\tparams: tensor([  4.8500, -14.3740])\n",
      "Epoch: 1053,Loss: 3.679969\n",
      "\tgrad: tensor([-0.0879,  0.4979])\n",
      "\tparams: tensor([  4.8509, -14.3790])\n",
      "Epoch: 1054,Loss: 3.677417\n",
      "\tgrad: tensor([-0.0878,  0.4970])\n",
      "\tparams: tensor([  4.8518, -14.3840])\n",
      "Epoch: 1055,Loss: 3.674871\n",
      "\tgrad: tensor([-0.0877,  0.4962])\n",
      "\tparams: tensor([  4.8526, -14.3889])\n",
      "Epoch: 1056,Loss: 3.672335\n",
      "\tgrad: tensor([-0.0875,  0.4953])\n",
      "\tparams: tensor([  4.8535, -14.3939])\n",
      "Epoch: 1057,Loss: 3.669804\n",
      "\tgrad: tensor([-0.0873,  0.4945])\n",
      "\tparams: tensor([  4.8544, -14.3988])\n",
      "Epoch: 1058,Loss: 3.667287\n",
      "\tgrad: tensor([-0.0872,  0.4936])\n",
      "\tparams: tensor([  4.8552, -14.4038])\n",
      "Epoch: 1059,Loss: 3.664775\n",
      "\tgrad: tensor([-0.0870,  0.4928])\n",
      "\tparams: tensor([  4.8561, -14.4087])\n",
      "Epoch: 1060,Loss: 3.662273\n",
      "\tgrad: tensor([-0.0869,  0.4920])\n",
      "\tparams: tensor([  4.8570, -14.4136])\n",
      "Epoch: 1061,Loss: 3.659778\n",
      "\tgrad: tensor([-0.0868,  0.4911])\n",
      "\tparams: tensor([  4.8579, -14.4185])\n",
      "Epoch: 1062,Loss: 3.657295\n",
      "\tgrad: tensor([-0.0866,  0.4903])\n",
      "\tparams: tensor([  4.8587, -14.4234])\n",
      "Epoch: 1063,Loss: 3.654816\n",
      "\tgrad: tensor([-0.0865,  0.4895])\n",
      "\tparams: tensor([  4.8596, -14.4283])\n",
      "Epoch: 1064,Loss: 3.652349\n",
      "\tgrad: tensor([-0.0863,  0.4886])\n",
      "\tparams: tensor([  4.8604, -14.4332])\n",
      "Epoch: 1065,Loss: 3.649889\n",
      "\tgrad: tensor([-0.0862,  0.4878])\n",
      "\tparams: tensor([  4.8613, -14.4381])\n",
      "Epoch: 1066,Loss: 3.647437\n",
      "\tgrad: tensor([-0.0860,  0.4870])\n",
      "\tparams: tensor([  4.8622, -14.4430])\n",
      "Epoch: 1067,Loss: 3.644991\n",
      "\tgrad: tensor([-0.0859,  0.4862])\n",
      "\tparams: tensor([  4.8630, -14.4478])\n",
      "Epoch: 1068,Loss: 3.642559\n",
      "\tgrad: tensor([-0.0857,  0.4853])\n",
      "\tparams: tensor([  4.8639, -14.4527])\n",
      "Epoch: 1069,Loss: 3.640132\n",
      "\tgrad: tensor([-0.0856,  0.4845])\n",
      "\tparams: tensor([  4.8647, -14.4575])\n",
      "Epoch: 1070,Loss: 3.637711\n",
      "\tgrad: tensor([-0.0854,  0.4837])\n",
      "\tparams: tensor([  4.8656, -14.4624])\n",
      "Epoch: 1071,Loss: 3.635302\n",
      "\tgrad: tensor([-0.0853,  0.4829])\n",
      "\tparams: tensor([  4.8665, -14.4672])\n",
      "Epoch: 1072,Loss: 3.632902\n",
      "\tgrad: tensor([-0.0851,  0.4820])\n",
      "\tparams: tensor([  4.8673, -14.4720])\n",
      "Epoch: 1073,Loss: 3.630508\n",
      "\tgrad: tensor([-0.0850,  0.4812])\n",
      "\tparams: tensor([  4.8682, -14.4768])\n",
      "Epoch: 1074,Loss: 3.628119\n",
      "\tgrad: tensor([-0.0849,  0.4804])\n",
      "\tparams: tensor([  4.8690, -14.4816])\n",
      "Epoch: 1075,Loss: 3.625741\n",
      "\tgrad: tensor([-0.0847,  0.4796])\n",
      "\tparams: tensor([  4.8698, -14.4864])\n",
      "Epoch: 1076,Loss: 3.623374\n",
      "\tgrad: tensor([-0.0846,  0.4788])\n",
      "\tparams: tensor([  4.8707, -14.4912])\n",
      "Epoch: 1077,Loss: 3.621010\n",
      "\tgrad: tensor([-0.0844,  0.4780])\n",
      "\tparams: tensor([  4.8715, -14.4960])\n",
      "Epoch: 1078,Loss: 3.618659\n",
      "\tgrad: tensor([-0.0843,  0.4771])\n",
      "\tparams: tensor([  4.8724, -14.5008])\n",
      "Epoch: 1079,Loss: 3.616311\n",
      "\tgrad: tensor([-0.0841,  0.4763])\n",
      "\tparams: tensor([  4.8732, -14.5055])\n",
      "Epoch: 1080,Loss: 3.613973\n",
      "\tgrad: tensor([-0.0840,  0.4755])\n",
      "\tparams: tensor([  4.8741, -14.5103])\n",
      "Epoch: 1081,Loss: 3.611643\n",
      "\tgrad: tensor([-0.0839,  0.4747])\n",
      "\tparams: tensor([  4.8749, -14.5150])\n",
      "Epoch: 1082,Loss: 3.609321\n",
      "\tgrad: tensor([-0.0837,  0.4739])\n",
      "\tparams: tensor([  4.8757, -14.5198])\n",
      "Epoch: 1083,Loss: 3.607008\n",
      "\tgrad: tensor([-0.0836,  0.4731])\n",
      "\tparams: tensor([  4.8766, -14.5245])\n",
      "Epoch: 1084,Loss: 3.604701\n",
      "\tgrad: tensor([-0.0834,  0.4723])\n",
      "\tparams: tensor([  4.8774, -14.5292])\n",
      "Epoch: 1085,Loss: 3.602403\n",
      "\tgrad: tensor([-0.0833,  0.4715])\n",
      "\tparams: tensor([  4.8782, -14.5339])\n",
      "Epoch: 1086,Loss: 3.600114\n",
      "\tgrad: tensor([-0.0832,  0.4707])\n",
      "\tparams: tensor([  4.8791, -14.5387])\n",
      "Epoch: 1087,Loss: 3.597831\n",
      "\tgrad: tensor([-0.0830,  0.4699])\n",
      "\tparams: tensor([  4.8799, -14.5434])\n",
      "Epoch: 1088,Loss: 3.595553\n",
      "\tgrad: tensor([-0.0829,  0.4691])\n",
      "\tparams: tensor([  4.8807, -14.5480])\n",
      "Epoch: 1089,Loss: 3.593287\n",
      "\tgrad: tensor([-0.0827,  0.4683])\n",
      "\tparams: tensor([  4.8816, -14.5527])\n",
      "Epoch: 1090,Loss: 3.591030\n",
      "\tgrad: tensor([-0.0826,  0.4675])\n",
      "\tparams: tensor([  4.8824, -14.5574])\n",
      "Epoch: 1091,Loss: 3.588776\n",
      "\tgrad: tensor([-0.0824,  0.4667])\n",
      "\tparams: tensor([  4.8832, -14.5621])\n",
      "Epoch: 1092,Loss: 3.586534\n",
      "\tgrad: tensor([-0.0823,  0.4659])\n",
      "\tparams: tensor([  4.8840, -14.5667])\n",
      "Epoch: 1093,Loss: 3.584294\n",
      "\tgrad: tensor([-0.0822,  0.4651])\n",
      "\tparams: tensor([  4.8849, -14.5714])\n",
      "Epoch: 1094,Loss: 3.582067\n",
      "\tgrad: tensor([-0.0820,  0.4643])\n",
      "\tparams: tensor([  4.8857, -14.5760])\n",
      "Epoch: 1095,Loss: 3.579845\n",
      "\tgrad: tensor([-0.0819,  0.4636])\n",
      "\tparams: tensor([  4.8865, -14.5807])\n",
      "Epoch: 1096,Loss: 3.577631\n",
      "\tgrad: tensor([-0.0818,  0.4628])\n",
      "\tparams: tensor([  4.8873, -14.5853])\n",
      "Epoch: 1097,Loss: 3.575424\n",
      "\tgrad: tensor([-0.0816,  0.4620])\n",
      "\tparams: tensor([  4.8881, -14.5899])\n",
      "Epoch: 1098,Loss: 3.573225\n",
      "\tgrad: tensor([-0.0815,  0.4612])\n",
      "\tparams: tensor([  4.8889, -14.5945])\n",
      "Epoch: 1099,Loss: 3.571035\n",
      "\tgrad: tensor([-0.0813,  0.4604])\n",
      "\tparams: tensor([  4.8898, -14.5991])\n",
      "Epoch: 1100,Loss: 3.568848\n",
      "\tgrad: tensor([-0.0812,  0.4596])\n",
      "\tparams: tensor([  4.8906, -14.6037])\n",
      "Epoch: 1101,Loss: 3.566673\n",
      "\tgrad: tensor([-0.0810,  0.4588])\n",
      "\tparams: tensor([  4.8914, -14.6083])\n",
      "Epoch: 1102,Loss: 3.564506\n",
      "\tgrad: tensor([-0.0809,  0.4581])\n",
      "\tparams: tensor([  4.8922, -14.6129])\n",
      "Epoch: 1103,Loss: 3.562341\n",
      "\tgrad: tensor([-0.0808,  0.4573])\n",
      "\tparams: tensor([  4.8930, -14.6175])\n",
      "Epoch: 1104,Loss: 3.560185\n",
      "\tgrad: tensor([-0.0806,  0.4565])\n",
      "\tparams: tensor([  4.8938, -14.6220])\n",
      "Epoch: 1105,Loss: 3.558040\n",
      "\tgrad: tensor([-0.0805,  0.4557])\n",
      "\tparams: tensor([  4.8946, -14.6266])\n",
      "Epoch: 1106,Loss: 3.555901\n",
      "\tgrad: tensor([-0.0804,  0.4550])\n",
      "\tparams: tensor([  4.8954, -14.6311])\n",
      "Epoch: 1107,Loss: 3.553767\n",
      "\tgrad: tensor([-0.0802,  0.4542])\n",
      "\tparams: tensor([  4.8962, -14.6357])\n",
      "Epoch: 1108,Loss: 3.551641\n",
      "\tgrad: tensor([-0.0801,  0.4534])\n",
      "\tparams: tensor([  4.8970, -14.6402])\n",
      "Epoch: 1109,Loss: 3.549524\n",
      "\tgrad: tensor([-0.0799,  0.4527])\n",
      "\tparams: tensor([  4.8978, -14.6447])\n",
      "Epoch: 1110,Loss: 3.547411\n",
      "\tgrad: tensor([-0.0798,  0.4519])\n",
      "\tparams: tensor([  4.8986, -14.6493])\n",
      "Epoch: 1111,Loss: 3.545309\n",
      "\tgrad: tensor([-0.0797,  0.4511])\n",
      "\tparams: tensor([  4.8994, -14.6538])\n",
      "Epoch: 1112,Loss: 3.543211\n",
      "\tgrad: tensor([-0.0796,  0.4503])\n",
      "\tparams: tensor([  4.9002, -14.6583])\n",
      "Epoch: 1113,Loss: 3.541124\n",
      "\tgrad: tensor([-0.0794,  0.4496])\n",
      "\tparams: tensor([  4.9010, -14.6628])\n",
      "Epoch: 1114,Loss: 3.539041\n",
      "\tgrad: tensor([-0.0793,  0.4488])\n",
      "\tparams: tensor([  4.9018, -14.6673])\n",
      "Epoch: 1115,Loss: 3.536967\n",
      "\tgrad: tensor([-0.0791,  0.4481])\n",
      "\tparams: tensor([  4.9026, -14.6717])\n",
      "Epoch: 1116,Loss: 3.534896\n",
      "\tgrad: tensor([-0.0790,  0.4473])\n",
      "\tparams: tensor([  4.9034, -14.6762])\n",
      "Epoch: 1117,Loss: 3.532835\n",
      "\tgrad: tensor([-0.0789,  0.4465])\n",
      "\tparams: tensor([  4.9042, -14.6807])\n",
      "Epoch: 1118,Loss: 3.530781\n",
      "\tgrad: tensor([-0.0787,  0.4458])\n",
      "\tparams: tensor([  4.9049, -14.6851])\n",
      "Epoch: 1119,Loss: 3.528734\n",
      "\tgrad: tensor([-0.0786,  0.4450])\n",
      "\tparams: tensor([  4.9057, -14.6896])\n",
      "Epoch: 1120,Loss: 3.526694\n",
      "\tgrad: tensor([-0.0785,  0.4443])\n",
      "\tparams: tensor([  4.9065, -14.6940])\n",
      "Epoch: 1121,Loss: 3.524662\n",
      "\tgrad: tensor([-0.0784,  0.4435])\n",
      "\tparams: tensor([  4.9073, -14.6985])\n",
      "Epoch: 1122,Loss: 3.522633\n",
      "\tgrad: tensor([-0.0782,  0.4428])\n",
      "\tparams: tensor([  4.9081, -14.7029])\n",
      "Epoch: 1123,Loss: 3.520614\n",
      "\tgrad: tensor([-0.0781,  0.4420])\n",
      "\tparams: tensor([  4.9089, -14.7073])\n",
      "Epoch: 1124,Loss: 3.518601\n",
      "\tgrad: tensor([-0.0779,  0.4413])\n",
      "\tparams: tensor([  4.9096, -14.7117])\n",
      "Epoch: 1125,Loss: 3.516594\n",
      "\tgrad: tensor([-0.0778,  0.4405])\n",
      "\tparams: tensor([  4.9104, -14.7161])\n",
      "Epoch: 1126,Loss: 3.514594\n",
      "\tgrad: tensor([-0.0777,  0.4398])\n",
      "\tparams: tensor([  4.9112, -14.7205])\n",
      "Epoch: 1127,Loss: 3.512602\n",
      "\tgrad: tensor([-0.0775,  0.4390])\n",
      "\tparams: tensor([  4.9120, -14.7249])\n",
      "Epoch: 1128,Loss: 3.510619\n",
      "\tgrad: tensor([-0.0774,  0.4383])\n",
      "\tparams: tensor([  4.9128, -14.7293])\n",
      "Epoch: 1129,Loss: 3.508637\n",
      "\tgrad: tensor([-0.0773,  0.4375])\n",
      "\tparams: tensor([  4.9135, -14.7337])\n",
      "Epoch: 1130,Loss: 3.506665\n",
      "\tgrad: tensor([-0.0772,  0.4368])\n",
      "\tparams: tensor([  4.9143, -14.7380])\n",
      "Epoch: 1131,Loss: 3.504699\n",
      "\tgrad: tensor([-0.0770,  0.4360])\n",
      "\tparams: tensor([  4.9151, -14.7424])\n",
      "Epoch: 1132,Loss: 3.502741\n",
      "\tgrad: tensor([-0.0769,  0.4353])\n",
      "\tparams: tensor([  4.9158, -14.7467])\n",
      "Epoch: 1133,Loss: 3.500789\n",
      "\tgrad: tensor([-0.0767,  0.4346])\n",
      "\tparams: tensor([  4.9166, -14.7511])\n",
      "Epoch: 1134,Loss: 3.498843\n",
      "\tgrad: tensor([-0.0766,  0.4338])\n",
      "\tparams: tensor([  4.9174, -14.7554])\n",
      "Epoch: 1135,Loss: 3.496905\n",
      "\tgrad: tensor([-0.0765,  0.4331])\n",
      "\tparams: tensor([  4.9181, -14.7598])\n",
      "Epoch: 1136,Loss: 3.494972\n",
      "\tgrad: tensor([-0.0764,  0.4323])\n",
      "\tparams: tensor([  4.9189, -14.7641])\n",
      "Epoch: 1137,Loss: 3.493046\n",
      "\tgrad: tensor([-0.0763,  0.4316])\n",
      "\tparams: tensor([  4.9197, -14.7684])\n",
      "Epoch: 1138,Loss: 3.491127\n",
      "\tgrad: tensor([-0.0761,  0.4309])\n",
      "\tparams: tensor([  4.9204, -14.7727])\n",
      "Epoch: 1139,Loss: 3.489214\n",
      "\tgrad: tensor([-0.0760,  0.4301])\n",
      "\tparams: tensor([  4.9212, -14.7770])\n",
      "Epoch: 1140,Loss: 3.487308\n",
      "\tgrad: tensor([-0.0759,  0.4294])\n",
      "\tparams: tensor([  4.9219, -14.7813])\n",
      "Epoch: 1141,Loss: 3.485410\n",
      "\tgrad: tensor([-0.0757,  0.4287])\n",
      "\tparams: tensor([  4.9227, -14.7856])\n",
      "Epoch: 1142,Loss: 3.483515\n",
      "\tgrad: tensor([-0.0756,  0.4280])\n",
      "\tparams: tensor([  4.9235, -14.7899])\n",
      "Epoch: 1143,Loss: 3.481627\n",
      "\tgrad: tensor([-0.0755,  0.4272])\n",
      "\tparams: tensor([  4.9242, -14.7941])\n",
      "Epoch: 1144,Loss: 3.479746\n",
      "\tgrad: tensor([-0.0753,  0.4265])\n",
      "\tparams: tensor([  4.9250, -14.7984])\n",
      "Epoch: 1145,Loss: 3.477872\n",
      "\tgrad: tensor([-0.0752,  0.4258])\n",
      "\tparams: tensor([  4.9257, -14.8027])\n",
      "Epoch: 1146,Loss: 3.476005\n",
      "\tgrad: tensor([-0.0751,  0.4250])\n",
      "\tparams: tensor([  4.9265, -14.8069])\n",
      "Epoch: 1147,Loss: 3.474143\n",
      "\tgrad: tensor([-0.0750,  0.4243])\n",
      "\tparams: tensor([  4.9272, -14.8112])\n",
      "Epoch: 1148,Loss: 3.472288\n",
      "\tgrad: tensor([-0.0748,  0.4236])\n",
      "\tparams: tensor([  4.9280, -14.8154])\n",
      "Epoch: 1149,Loss: 3.470441\n",
      "\tgrad: tensor([-0.0747,  0.4229])\n",
      "\tparams: tensor([  4.9287, -14.8196])\n",
      "Epoch: 1150,Loss: 3.468597\n",
      "\tgrad: tensor([-0.0746,  0.4222])\n",
      "\tparams: tensor([  4.9295, -14.8238])\n",
      "Epoch: 1151,Loss: 3.466762\n",
      "\tgrad: tensor([-0.0745,  0.4215])\n",
      "\tparams: tensor([  4.9302, -14.8281])\n",
      "Epoch: 1152,Loss: 3.464930\n",
      "\tgrad: tensor([-0.0743,  0.4207])\n",
      "\tparams: tensor([  4.9309, -14.8323])\n",
      "Epoch: 1153,Loss: 3.463105\n",
      "\tgrad: tensor([-0.0742,  0.4200])\n",
      "\tparams: tensor([  4.9317, -14.8365])\n",
      "Epoch: 1154,Loss: 3.461290\n",
      "\tgrad: tensor([-0.0741,  0.4193])\n",
      "\tparams: tensor([  4.9324, -14.8407])\n",
      "Epoch: 1155,Loss: 3.459477\n",
      "\tgrad: tensor([-0.0739,  0.4186])\n",
      "\tparams: tensor([  4.9332, -14.8448])\n",
      "Epoch: 1156,Loss: 3.457671\n",
      "\tgrad: tensor([-0.0738,  0.4179])\n",
      "\tparams: tensor([  4.9339, -14.8490])\n",
      "Epoch: 1157,Loss: 3.455873\n",
      "\tgrad: tensor([-0.0737,  0.4172])\n",
      "\tparams: tensor([  4.9346, -14.8532])\n",
      "Epoch: 1158,Loss: 3.454080\n",
      "\tgrad: tensor([-0.0736,  0.4165])\n",
      "\tparams: tensor([  4.9354, -14.8574])\n",
      "Epoch: 1159,Loss: 3.452293\n",
      "\tgrad: tensor([-0.0734,  0.4158])\n",
      "\tparams: tensor([  4.9361, -14.8615])\n",
      "Epoch: 1160,Loss: 3.450513\n",
      "\tgrad: tensor([-0.0733,  0.4151])\n",
      "\tparams: tensor([  4.9368, -14.8657])\n",
      "Epoch: 1161,Loss: 3.448736\n",
      "\tgrad: tensor([-0.0732,  0.4143])\n",
      "\tparams: tensor([  4.9376, -14.8698])\n",
      "Epoch: 1162,Loss: 3.446968\n",
      "\tgrad: tensor([-0.0731,  0.4136])\n",
      "\tparams: tensor([  4.9383, -14.8739])\n",
      "Epoch: 1163,Loss: 3.445203\n",
      "\tgrad: tensor([-0.0730,  0.4129])\n",
      "\tparams: tensor([  4.9390, -14.8781])\n",
      "Epoch: 1164,Loss: 3.443449\n",
      "\tgrad: tensor([-0.0728,  0.4122])\n",
      "\tparams: tensor([  4.9398, -14.8822])\n",
      "Epoch: 1165,Loss: 3.441697\n",
      "\tgrad: tensor([-0.0727,  0.4115])\n",
      "\tparams: tensor([  4.9405, -14.8863])\n",
      "Epoch: 1166,Loss: 3.439952\n",
      "\tgrad: tensor([-0.0726,  0.4108])\n",
      "\tparams: tensor([  4.9412, -14.8904])\n",
      "Epoch: 1167,Loss: 3.438210\n",
      "\tgrad: tensor([-0.0725,  0.4101])\n",
      "\tparams: tensor([  4.9419, -14.8945])\n",
      "Epoch: 1168,Loss: 3.436479\n",
      "\tgrad: tensor([-0.0723,  0.4094])\n",
      "\tparams: tensor([  4.9427, -14.8986])\n",
      "Epoch: 1169,Loss: 3.434753\n",
      "\tgrad: tensor([-0.0722,  0.4087])\n",
      "\tparams: tensor([  4.9434, -14.9027])\n",
      "Epoch: 1170,Loss: 3.433030\n",
      "\tgrad: tensor([-0.0721,  0.4081])\n",
      "\tparams: tensor([  4.9441, -14.9068])\n",
      "Epoch: 1171,Loss: 3.431314\n",
      "\tgrad: tensor([-0.0720,  0.4074])\n",
      "\tparams: tensor([  4.9448, -14.9109])\n",
      "Epoch: 1172,Loss: 3.429607\n",
      "\tgrad: tensor([-0.0719,  0.4067])\n",
      "\tparams: tensor([  4.9455, -14.9149])\n",
      "Epoch: 1173,Loss: 3.427903\n",
      "\tgrad: tensor([-0.0717,  0.4060])\n",
      "\tparams: tensor([  4.9463, -14.9190])\n",
      "Epoch: 1174,Loss: 3.426204\n",
      "\tgrad: tensor([-0.0716,  0.4053])\n",
      "\tparams: tensor([  4.9470, -14.9230])\n",
      "Epoch: 1175,Loss: 3.424510\n",
      "\tgrad: tensor([-0.0715,  0.4046])\n",
      "\tparams: tensor([  4.9477, -14.9271])\n",
      "Epoch: 1176,Loss: 3.422823\n",
      "\tgrad: tensor([-0.0714,  0.4039])\n",
      "\tparams: tensor([  4.9484, -14.9311])\n",
      "Epoch: 1177,Loss: 3.421144\n",
      "\tgrad: tensor([-0.0712,  0.4032])\n",
      "\tparams: tensor([  4.9491, -14.9352])\n",
      "Epoch: 1178,Loss: 3.419468\n",
      "\tgrad: tensor([-0.0711,  0.4025])\n",
      "\tparams: tensor([  4.9498, -14.9392])\n",
      "Epoch: 1179,Loss: 3.417798\n",
      "\tgrad: tensor([-0.0710,  0.4019])\n",
      "\tparams: tensor([  4.9505, -14.9432])\n",
      "Epoch: 1180,Loss: 3.416134\n",
      "\tgrad: tensor([-0.0709,  0.4012])\n",
      "\tparams: tensor([  4.9512, -14.9472])\n",
      "Epoch: 1181,Loss: 3.414476\n",
      "\tgrad: tensor([-0.0708,  0.4005])\n",
      "\tparams: tensor([  4.9520, -14.9512])\n",
      "Epoch: 1182,Loss: 3.412824\n",
      "\tgrad: tensor([-0.0706,  0.3998])\n",
      "\tparams: tensor([  4.9527, -14.9552])\n",
      "Epoch: 1183,Loss: 3.411176\n",
      "\tgrad: tensor([-0.0705,  0.3991])\n",
      "\tparams: tensor([  4.9534, -14.9592])\n",
      "Epoch: 1184,Loss: 3.409534\n",
      "\tgrad: tensor([-0.0704,  0.3985])\n",
      "\tparams: tensor([  4.9541, -14.9632])\n",
      "Epoch: 1185,Loss: 3.407900\n",
      "\tgrad: tensor([-0.0703,  0.3978])\n",
      "\tparams: tensor([  4.9548, -14.9672])\n",
      "Epoch: 1186,Loss: 3.406271\n",
      "\tgrad: tensor([-0.0701,  0.3971])\n",
      "\tparams: tensor([  4.9555, -14.9711])\n",
      "Epoch: 1187,Loss: 3.404645\n",
      "\tgrad: tensor([-0.0700,  0.3964])\n",
      "\tparams: tensor([  4.9562, -14.9751])\n",
      "Epoch: 1188,Loss: 3.403024\n",
      "\tgrad: tensor([-0.0699,  0.3958])\n",
      "\tparams: tensor([  4.9569, -14.9791])\n",
      "Epoch: 1189,Loss: 3.401413\n",
      "\tgrad: tensor([-0.0698,  0.3951])\n",
      "\tparams: tensor([  4.9576, -14.9830])\n",
      "Epoch: 1190,Loss: 3.399802\n",
      "\tgrad: tensor([-0.0697,  0.3944])\n",
      "\tparams: tensor([  4.9583, -14.9870])\n",
      "Epoch: 1191,Loss: 3.398200\n",
      "\tgrad: tensor([-0.0696,  0.3937])\n",
      "\tparams: tensor([  4.9590, -14.9909])\n",
      "Epoch: 1192,Loss: 3.396602\n",
      "\tgrad: tensor([-0.0694,  0.3931])\n",
      "\tparams: tensor([  4.9597, -14.9948])\n",
      "Epoch: 1193,Loss: 3.395011\n",
      "\tgrad: tensor([-0.0693,  0.3924])\n",
      "\tparams: tensor([  4.9604, -14.9988])\n",
      "Epoch: 1194,Loss: 3.393425\n",
      "\tgrad: tensor([-0.0692,  0.3917])\n",
      "\tparams: tensor([  4.9610, -15.0027])\n",
      "Epoch: 1195,Loss: 3.391844\n",
      "\tgrad: tensor([-0.0691,  0.3911])\n",
      "\tparams: tensor([  4.9617, -15.0066])\n",
      "Epoch: 1196,Loss: 3.390266\n",
      "\tgrad: tensor([-0.0690,  0.3904])\n",
      "\tparams: tensor([  4.9624, -15.0105])\n",
      "Epoch: 1197,Loss: 3.388697\n",
      "\tgrad: tensor([-0.0689,  0.3897])\n",
      "\tparams: tensor([  4.9631, -15.0144])\n",
      "Epoch: 1198,Loss: 3.387131\n",
      "\tgrad: tensor([-0.0687,  0.3891])\n",
      "\tparams: tensor([  4.9638, -15.0183])\n",
      "Epoch: 1199,Loss: 3.385571\n",
      "\tgrad: tensor([-0.0686,  0.3884])\n",
      "\tparams: tensor([  4.9645, -15.0222])\n",
      "Epoch: 1200,Loss: 3.384018\n",
      "\tgrad: tensor([-0.0685,  0.3878])\n",
      "\tparams: tensor([  4.9652, -15.0260])\n",
      "Epoch: 1201,Loss: 3.382467\n",
      "\tgrad: tensor([-0.0684,  0.3871])\n",
      "\tparams: tensor([  4.9659, -15.0299])\n",
      "Epoch: 1202,Loss: 3.380925\n",
      "\tgrad: tensor([-0.0683,  0.3864])\n",
      "\tparams: tensor([  4.9665, -15.0338])\n",
      "Epoch: 1203,Loss: 3.379385\n",
      "\tgrad: tensor([-0.0681,  0.3858])\n",
      "\tparams: tensor([  4.9672, -15.0376])\n",
      "Epoch: 1204,Loss: 3.377851\n",
      "\tgrad: tensor([-0.0680,  0.3851])\n",
      "\tparams: tensor([  4.9679, -15.0415])\n",
      "Epoch: 1205,Loss: 3.376323\n",
      "\tgrad: tensor([-0.0679,  0.3845])\n",
      "\tparams: tensor([  4.9686, -15.0453])\n",
      "Epoch: 1206,Loss: 3.374800\n",
      "\tgrad: tensor([-0.0678,  0.3838])\n",
      "\tparams: tensor([  4.9693, -15.0492])\n",
      "Epoch: 1207,Loss: 3.373284\n",
      "\tgrad: tensor([-0.0677,  0.3832])\n",
      "\tparams: tensor([  4.9699, -15.0530])\n",
      "Epoch: 1208,Loss: 3.371769\n",
      "\tgrad: tensor([-0.0676,  0.3825])\n",
      "\tparams: tensor([  4.9706, -15.0568])\n",
      "Epoch: 1209,Loss: 3.370261\n",
      "\tgrad: tensor([-0.0675,  0.3819])\n",
      "\tparams: tensor([  4.9713, -15.0606])\n",
      "Epoch: 1210,Loss: 3.368760\n",
      "\tgrad: tensor([-0.0673,  0.3812])\n",
      "\tparams: tensor([  4.9720, -15.0645])\n",
      "Epoch: 1211,Loss: 3.367262\n",
      "\tgrad: tensor([-0.0672,  0.3806])\n",
      "\tparams: tensor([  4.9726, -15.0683])\n",
      "Epoch: 1212,Loss: 3.365771\n",
      "\tgrad: tensor([-0.0671,  0.3799])\n",
      "\tparams: tensor([  4.9733, -15.0721])\n",
      "Epoch: 1213,Loss: 3.364282\n",
      "\tgrad: tensor([-0.0670,  0.3793])\n",
      "\tparams: tensor([  4.9740, -15.0758])\n",
      "Epoch: 1214,Loss: 3.362800\n",
      "\tgrad: tensor([-0.0669,  0.3786])\n",
      "\tparams: tensor([  4.9746, -15.0796])\n",
      "Epoch: 1215,Loss: 3.361324\n",
      "\tgrad: tensor([-0.0668,  0.3780])\n",
      "\tparams: tensor([  4.9753, -15.0834])\n",
      "Epoch: 1216,Loss: 3.359850\n",
      "\tgrad: tensor([-0.0667,  0.3774])\n",
      "\tparams: tensor([  4.9760, -15.0872])\n",
      "Epoch: 1217,Loss: 3.358384\n",
      "\tgrad: tensor([-0.0665,  0.3767])\n",
      "\tparams: tensor([  4.9766, -15.0910])\n",
      "Epoch: 1218,Loss: 3.356921\n",
      "\tgrad: tensor([-0.0664,  0.3761])\n",
      "\tparams: tensor([  4.9773, -15.0947])\n",
      "Epoch: 1219,Loss: 3.355464\n",
      "\tgrad: tensor([-0.0663,  0.3754])\n",
      "\tparams: tensor([  4.9780, -15.0985])\n",
      "Epoch: 1220,Loss: 3.354012\n",
      "\tgrad: tensor([-0.0662,  0.3748])\n",
      "\tparams: tensor([  4.9786, -15.1022])\n",
      "Epoch: 1221,Loss: 3.352564\n",
      "\tgrad: tensor([-0.0661,  0.3742])\n",
      "\tparams: tensor([  4.9793, -15.1060])\n",
      "Epoch: 1222,Loss: 3.351122\n",
      "\tgrad: tensor([-0.0660,  0.3735])\n",
      "\tparams: tensor([  4.9799, -15.1097])\n",
      "Epoch: 1223,Loss: 3.349685\n",
      "\tgrad: tensor([-0.0659,  0.3729])\n",
      "\tparams: tensor([  4.9806, -15.1134])\n",
      "Epoch: 1224,Loss: 3.348251\n",
      "\tgrad: tensor([-0.0657,  0.3723])\n",
      "\tparams: tensor([  4.9813, -15.1171])\n",
      "Epoch: 1225,Loss: 3.346824\n",
      "\tgrad: tensor([-0.0656,  0.3716])\n",
      "\tparams: tensor([  4.9819, -15.1209])\n",
      "Epoch: 1226,Loss: 3.345403\n",
      "\tgrad: tensor([-0.0655,  0.3710])\n",
      "\tparams: tensor([  4.9826, -15.1246])\n",
      "Epoch: 1227,Loss: 3.343982\n",
      "\tgrad: tensor([-0.0654,  0.3704])\n",
      "\tparams: tensor([  4.9832, -15.1283])\n",
      "Epoch: 1228,Loss: 3.342571\n",
      "\tgrad: tensor([-0.0653,  0.3697])\n",
      "\tparams: tensor([  4.9839, -15.1320])\n",
      "Epoch: 1229,Loss: 3.341160\n",
      "\tgrad: tensor([-0.0652,  0.3691])\n",
      "\tparams: tensor([  4.9845, -15.1357])\n",
      "Epoch: 1230,Loss: 3.339758\n",
      "\tgrad: tensor([-0.0651,  0.3685])\n",
      "\tparams: tensor([  4.9852, -15.1393])\n",
      "Epoch: 1231,Loss: 3.338359\n",
      "\tgrad: tensor([-0.0650,  0.3679])\n",
      "\tparams: tensor([  4.9858, -15.1430])\n",
      "Epoch: 1232,Loss: 3.336965\n",
      "\tgrad: tensor([-0.0649,  0.3672])\n",
      "\tparams: tensor([  4.9865, -15.1467])\n",
      "Epoch: 1233,Loss: 3.335577\n",
      "\tgrad: tensor([-0.0648,  0.3666])\n",
      "\tparams: tensor([  4.9871, -15.1504])\n",
      "Epoch: 1234,Loss: 3.334192\n",
      "\tgrad: tensor([-0.0646,  0.3660])\n",
      "\tparams: tensor([  4.9878, -15.1540])\n",
      "Epoch: 1235,Loss: 3.332811\n",
      "\tgrad: tensor([-0.0645,  0.3654])\n",
      "\tparams: tensor([  4.9884, -15.1577])\n",
      "Epoch: 1236,Loss: 3.331436\n",
      "\tgrad: tensor([-0.0644,  0.3647])\n",
      "\tparams: tensor([  4.9891, -15.1613])\n",
      "Epoch: 1237,Loss: 3.330065\n",
      "\tgrad: tensor([-0.0643,  0.3641])\n",
      "\tparams: tensor([  4.9897, -15.1650])\n",
      "Epoch: 1238,Loss: 3.328699\n",
      "\tgrad: tensor([-0.0642,  0.3635])\n",
      "\tparams: tensor([  4.9904, -15.1686])\n",
      "Epoch: 1239,Loss: 3.327339\n",
      "\tgrad: tensor([-0.0641,  0.3629])\n",
      "\tparams: tensor([  4.9910, -15.1722])\n",
      "Epoch: 1240,Loss: 3.325980\n",
      "\tgrad: tensor([-0.0640,  0.3623])\n",
      "\tparams: tensor([  4.9916, -15.1759])\n",
      "Epoch: 1241,Loss: 3.324628\n",
      "\tgrad: tensor([-0.0639,  0.3617])\n",
      "\tparams: tensor([  4.9923, -15.1795])\n",
      "Epoch: 1242,Loss: 3.323279\n",
      "\tgrad: tensor([-0.0638,  0.3610])\n",
      "\tparams: tensor([  4.9929, -15.1831])\n",
      "Epoch: 1243,Loss: 3.321935\n",
      "\tgrad: tensor([-0.0637,  0.3604])\n",
      "\tparams: tensor([  4.9936, -15.1867])\n",
      "Epoch: 1244,Loss: 3.320600\n",
      "\tgrad: tensor([-0.0636,  0.3598])\n",
      "\tparams: tensor([  4.9942, -15.1903])\n",
      "Epoch: 1245,Loss: 3.319264\n",
      "\tgrad: tensor([-0.0635,  0.3592])\n",
      "\tparams: tensor([  4.9948, -15.1939])\n",
      "Epoch: 1246,Loss: 3.317935\n",
      "\tgrad: tensor([-0.0633,  0.3586])\n",
      "\tparams: tensor([  4.9955, -15.1975])\n",
      "Epoch: 1247,Loss: 3.316611\n",
      "\tgrad: tensor([-0.0633,  0.3580])\n",
      "\tparams: tensor([  4.9961, -15.2010])\n",
      "Epoch: 1248,Loss: 3.315289\n",
      "\tgrad: tensor([-0.0631,  0.3574])\n",
      "\tparams: tensor([  4.9967, -15.2046])\n",
      "Epoch: 1249,Loss: 3.313973\n",
      "\tgrad: tensor([-0.0630,  0.3568])\n",
      "\tparams: tensor([  4.9973, -15.2082])\n",
      "Epoch: 1250,Loss: 3.312663\n",
      "\tgrad: tensor([-0.0629,  0.3562])\n",
      "\tparams: tensor([  4.9980, -15.2117])\n",
      "Epoch: 1251,Loss: 3.311353\n",
      "\tgrad: tensor([-0.0628,  0.3556])\n",
      "\tparams: tensor([  4.9986, -15.2153])\n",
      "Epoch: 1252,Loss: 3.310053\n",
      "\tgrad: tensor([-0.0627,  0.3550])\n",
      "\tparams: tensor([  4.9992, -15.2189])\n",
      "Epoch: 1253,Loss: 3.308756\n",
      "\tgrad: tensor([-0.0626,  0.3543])\n",
      "\tparams: tensor([  4.9999, -15.2224])\n",
      "Epoch: 1254,Loss: 3.307463\n",
      "\tgrad: tensor([-0.0625,  0.3537])\n",
      "\tparams: tensor([  5.0005, -15.2259])\n",
      "Epoch: 1255,Loss: 3.306170\n",
      "\tgrad: tensor([-0.0624,  0.3531])\n",
      "\tparams: tensor([  5.0011, -15.2295])\n",
      "Epoch: 1256,Loss: 3.304887\n",
      "\tgrad: tensor([-0.0623,  0.3525])\n",
      "\tparams: tensor([  5.0017, -15.2330])\n",
      "Epoch: 1257,Loss: 3.303605\n",
      "\tgrad: tensor([-0.0622,  0.3519])\n",
      "\tparams: tensor([  5.0024, -15.2365])\n",
      "Epoch: 1258,Loss: 3.302329\n",
      "\tgrad: tensor([-0.0620,  0.3514])\n",
      "\tparams: tensor([  5.0030, -15.2400])\n",
      "Epoch: 1259,Loss: 3.301057\n",
      "\tgrad: tensor([-0.0620,  0.3508])\n",
      "\tparams: tensor([  5.0036, -15.2435])\n",
      "Epoch: 1260,Loss: 3.299791\n",
      "\tgrad: tensor([-0.0619,  0.3502])\n",
      "\tparams: tensor([  5.0042, -15.2470])\n",
      "Epoch: 1261,Loss: 3.298528\n",
      "\tgrad: tensor([-0.0618,  0.3496])\n",
      "\tparams: tensor([  5.0048, -15.2505])\n",
      "Epoch: 1262,Loss: 3.297267\n",
      "\tgrad: tensor([-0.0616,  0.3490])\n",
      "\tparams: tensor([  5.0054, -15.2540])\n",
      "Epoch: 1263,Loss: 3.296014\n",
      "\tgrad: tensor([-0.0615,  0.3484])\n",
      "\tparams: tensor([  5.0061, -15.2575])\n",
      "Epoch: 1264,Loss: 3.294762\n",
      "\tgrad: tensor([-0.0614,  0.3478])\n",
      "\tparams: tensor([  5.0067, -15.2610])\n",
      "Epoch: 1265,Loss: 3.293517\n",
      "\tgrad: tensor([-0.0613,  0.3472])\n",
      "\tparams: tensor([  5.0073, -15.2645])\n",
      "Epoch: 1266,Loss: 3.292276\n",
      "\tgrad: tensor([-0.0612,  0.3466])\n",
      "\tparams: tensor([  5.0079, -15.2679])\n",
      "Epoch: 1267,Loss: 3.291036\n",
      "\tgrad: tensor([-0.0611,  0.3460])\n",
      "\tparams: tensor([  5.0085, -15.2714])\n",
      "Epoch: 1268,Loss: 3.289804\n",
      "\tgrad: tensor([-0.0610,  0.3454])\n",
      "\tparams: tensor([  5.0091, -15.2748])\n",
      "Epoch: 1269,Loss: 3.288573\n",
      "\tgrad: tensor([-0.0609,  0.3448])\n",
      "\tparams: tensor([  5.0097, -15.2783])\n",
      "Epoch: 1270,Loss: 3.287347\n",
      "\tgrad: tensor([-0.0608,  0.3443])\n",
      "\tparams: tensor([  5.0103, -15.2817])\n",
      "Epoch: 1271,Loss: 3.286129\n",
      "\tgrad: tensor([-0.0607,  0.3437])\n",
      "\tparams: tensor([  5.0109, -15.2852])\n",
      "Epoch: 1272,Loss: 3.284911\n",
      "\tgrad: tensor([-0.0606,  0.3431])\n",
      "\tparams: tensor([  5.0116, -15.2886])\n",
      "Epoch: 1273,Loss: 3.283698\n",
      "\tgrad: tensor([-0.0605,  0.3425])\n",
      "\tparams: tensor([  5.0122, -15.2920])\n",
      "Epoch: 1274,Loss: 3.282488\n",
      "\tgrad: tensor([-0.0604,  0.3419])\n",
      "\tparams: tensor([  5.0128, -15.2954])\n",
      "Epoch: 1275,Loss: 3.281284\n",
      "\tgrad: tensor([-0.0603,  0.3413])\n",
      "\tparams: tensor([  5.0134, -15.2988])\n",
      "Epoch: 1276,Loss: 3.280085\n",
      "\tgrad: tensor([-0.0602,  0.3408])\n",
      "\tparams: tensor([  5.0140, -15.3023])\n",
      "Epoch: 1277,Loss: 3.278888\n",
      "\tgrad: tensor([-0.0601,  0.3402])\n",
      "\tparams: tensor([  5.0146, -15.3057])\n",
      "Epoch: 1278,Loss: 3.277696\n",
      "\tgrad: tensor([-0.0600,  0.3396])\n",
      "\tparams: tensor([  5.0152, -15.3091])\n",
      "Epoch: 1279,Loss: 3.276506\n",
      "\tgrad: tensor([-0.0599,  0.3390])\n",
      "\tparams: tensor([  5.0158, -15.3124])\n",
      "Epoch: 1280,Loss: 3.275322\n",
      "\tgrad: tensor([-0.0598,  0.3384])\n",
      "\tparams: tensor([  5.0164, -15.3158])\n",
      "Epoch: 1281,Loss: 3.274142\n",
      "\tgrad: tensor([-0.0597,  0.3379])\n",
      "\tparams: tensor([  5.0170, -15.3192])\n",
      "Epoch: 1282,Loss: 3.272968\n",
      "\tgrad: tensor([-0.0596,  0.3373])\n",
      "\tparams: tensor([  5.0176, -15.3226])\n",
      "Epoch: 1283,Loss: 3.271793\n",
      "\tgrad: tensor([-0.0595,  0.3367])\n",
      "\tparams: tensor([  5.0182, -15.3259])\n",
      "Epoch: 1284,Loss: 3.270625\n",
      "\tgrad: tensor([-0.0594,  0.3362])\n",
      "\tparams: tensor([  5.0187, -15.3293])\n",
      "Epoch: 1285,Loss: 3.269460\n",
      "\tgrad: tensor([-0.0593,  0.3356])\n",
      "\tparams: tensor([  5.0193, -15.3327])\n",
      "Epoch: 1286,Loss: 3.268301\n",
      "\tgrad: tensor([-0.0592,  0.3350])\n",
      "\tparams: tensor([  5.0199, -15.3360])\n",
      "Epoch: 1287,Loss: 3.267143\n",
      "\tgrad: tensor([-0.0591,  0.3344])\n",
      "\tparams: tensor([  5.0205, -15.3394])\n",
      "Epoch: 1288,Loss: 3.265991\n",
      "\tgrad: tensor([-0.0590,  0.3339])\n",
      "\tparams: tensor([  5.0211, -15.3427])\n",
      "Epoch: 1289,Loss: 3.264842\n",
      "\tgrad: tensor([-0.0589,  0.3333])\n",
      "\tparams: tensor([  5.0217, -15.3460])\n",
      "Epoch: 1290,Loss: 3.263700\n",
      "\tgrad: tensor([-0.0588,  0.3327])\n",
      "\tparams: tensor([  5.0223, -15.3494])\n",
      "Epoch: 1291,Loss: 3.262556\n",
      "\tgrad: tensor([-0.0587,  0.3322])\n",
      "\tparams: tensor([  5.0229, -15.3527])\n",
      "Epoch: 1292,Loss: 3.261421\n",
      "\tgrad: tensor([-0.0586,  0.3316])\n",
      "\tparams: tensor([  5.0235, -15.3560])\n",
      "Epoch: 1293,Loss: 3.260287\n",
      "\tgrad: tensor([-0.0585,  0.3311])\n",
      "\tparams: tensor([  5.0240, -15.3593])\n",
      "Epoch: 1294,Loss: 3.259160\n",
      "\tgrad: tensor([-0.0584,  0.3305])\n",
      "\tparams: tensor([  5.0246, -15.3626])\n",
      "Epoch: 1295,Loss: 3.258033\n",
      "\tgrad: tensor([-0.0583,  0.3299])\n",
      "\tparams: tensor([  5.0252, -15.3659])\n",
      "Epoch: 1296,Loss: 3.256912\n",
      "\tgrad: tensor([-0.0582,  0.3294])\n",
      "\tparams: tensor([  5.0258, -15.3692])\n",
      "Epoch: 1297,Loss: 3.255795\n",
      "\tgrad: tensor([-0.0581,  0.3288])\n",
      "\tparams: tensor([  5.0264, -15.3725])\n",
      "Epoch: 1298,Loss: 3.254681\n",
      "\tgrad: tensor([-0.0580,  0.3282])\n",
      "\tparams: tensor([  5.0270, -15.3758])\n",
      "Epoch: 1299,Loss: 3.253569\n",
      "\tgrad: tensor([-0.0579,  0.3277])\n",
      "\tparams: tensor([  5.0275, -15.3791])\n",
      "Epoch: 1300,Loss: 3.252462\n",
      "\tgrad: tensor([-0.0578,  0.3271])\n",
      "\tparams: tensor([  5.0281, -15.3823])\n",
      "Epoch: 1301,Loss: 3.251362\n",
      "\tgrad: tensor([-0.0577,  0.3266])\n",
      "\tparams: tensor([  5.0287, -15.3856])\n",
      "Epoch: 1302,Loss: 3.250263\n",
      "\tgrad: tensor([-0.0576,  0.3260])\n",
      "\tparams: tensor([  5.0293, -15.3888])\n",
      "Epoch: 1303,Loss: 3.249168\n",
      "\tgrad: tensor([-0.0575,  0.3255])\n",
      "\tparams: tensor([  5.0298, -15.3921])\n",
      "Epoch: 1304,Loss: 3.248077\n",
      "\tgrad: tensor([-0.0574,  0.3249])\n",
      "\tparams: tensor([  5.0304, -15.3954])\n",
      "Epoch: 1305,Loss: 3.246988\n",
      "\tgrad: tensor([-0.0573,  0.3244])\n",
      "\tparams: tensor([  5.0310, -15.3986])\n",
      "Epoch: 1306,Loss: 3.245904\n",
      "\tgrad: tensor([-0.0572,  0.3238])\n",
      "\tparams: tensor([  5.0316, -15.4018])\n",
      "Epoch: 1307,Loss: 3.244824\n",
      "\tgrad: tensor([-0.0571,  0.3233])\n",
      "\tparams: tensor([  5.0321, -15.4051])\n",
      "Epoch: 1308,Loss: 3.243747\n",
      "\tgrad: tensor([-0.0570,  0.3227])\n",
      "\tparams: tensor([  5.0327, -15.4083])\n",
      "Epoch: 1309,Loss: 3.242674\n",
      "\tgrad: tensor([-0.0569,  0.3222])\n",
      "\tparams: tensor([  5.0333, -15.4115])\n",
      "Epoch: 1310,Loss: 3.241606\n",
      "\tgrad: tensor([-0.0568,  0.3216])\n",
      "\tparams: tensor([  5.0338, -15.4147])\n",
      "Epoch: 1311,Loss: 3.240538\n",
      "\tgrad: tensor([-0.0567,  0.3211])\n",
      "\tparams: tensor([  5.0344, -15.4179])\n",
      "Epoch: 1312,Loss: 3.239475\n",
      "\tgrad: tensor([-0.0566,  0.3205])\n",
      "\tparams: tensor([  5.0350, -15.4211])\n",
      "Epoch: 1313,Loss: 3.238419\n",
      "\tgrad: tensor([-0.0565,  0.3200])\n",
      "\tparams: tensor([  5.0355, -15.4243])\n",
      "Epoch: 1314,Loss: 3.237363\n",
      "\tgrad: tensor([-0.0564,  0.3194])\n",
      "\tparams: tensor([  5.0361, -15.4275])\n",
      "Epoch: 1315,Loss: 3.236314\n",
      "\tgrad: tensor([-0.0563,  0.3189])\n",
      "\tparams: tensor([  5.0367, -15.4307])\n",
      "Epoch: 1316,Loss: 3.235265\n",
      "\tgrad: tensor([-0.0562,  0.3184])\n",
      "\tparams: tensor([  5.0372, -15.4339])\n",
      "Epoch: 1317,Loss: 3.234218\n",
      "\tgrad: tensor([-0.0561,  0.3178])\n",
      "\tparams: tensor([  5.0378, -15.4371])\n",
      "Epoch: 1318,Loss: 3.233179\n",
      "\tgrad: tensor([-0.0561,  0.3173])\n",
      "\tparams: tensor([  5.0383, -15.4403])\n",
      "Epoch: 1319,Loss: 3.232143\n",
      "\tgrad: tensor([-0.0560,  0.3167])\n",
      "\tparams: tensor([  5.0389, -15.4434])\n",
      "Epoch: 1320,Loss: 3.231109\n",
      "\tgrad: tensor([-0.0558,  0.3162])\n",
      "\tparams: tensor([  5.0395, -15.4466])\n",
      "Epoch: 1321,Loss: 3.230078\n",
      "\tgrad: tensor([-0.0558,  0.3157])\n",
      "\tparams: tensor([  5.0400, -15.4498])\n",
      "Epoch: 1322,Loss: 3.229051\n",
      "\tgrad: tensor([-0.0557,  0.3151])\n",
      "\tparams: tensor([  5.0406, -15.4529])\n",
      "Epoch: 1323,Loss: 3.228027\n",
      "\tgrad: tensor([-0.0556,  0.3146])\n",
      "\tparams: tensor([  5.0411, -15.4560])\n",
      "Epoch: 1324,Loss: 3.227010\n",
      "\tgrad: tensor([-0.0555,  0.3141])\n",
      "\tparams: tensor([  5.0417, -15.4592])\n",
      "Epoch: 1325,Loss: 3.225992\n",
      "\tgrad: tensor([-0.0554,  0.3135])\n",
      "\tparams: tensor([  5.0422, -15.4623])\n",
      "Epoch: 1326,Loss: 3.224979\n",
      "\tgrad: tensor([-0.0553,  0.3130])\n",
      "\tparams: tensor([  5.0428, -15.4655])\n",
      "Epoch: 1327,Loss: 3.223971\n",
      "\tgrad: tensor([-0.0552,  0.3125])\n",
      "\tparams: tensor([  5.0433, -15.4686])\n",
      "Epoch: 1328,Loss: 3.222965\n",
      "\tgrad: tensor([-0.0551,  0.3119])\n",
      "\tparams: tensor([  5.0439, -15.4717])\n",
      "Epoch: 1329,Loss: 3.221960\n",
      "\tgrad: tensor([-0.0550,  0.3114])\n",
      "\tparams: tensor([  5.0444, -15.4748])\n",
      "Epoch: 1330,Loss: 3.220962\n",
      "\tgrad: tensor([-0.0549,  0.3109])\n",
      "\tparams: tensor([  5.0450, -15.4779])\n",
      "Epoch: 1331,Loss: 3.219967\n",
      "\tgrad: tensor([-0.0548,  0.3103])\n",
      "\tparams: tensor([  5.0455, -15.4810])\n",
      "Epoch: 1332,Loss: 3.218975\n",
      "\tgrad: tensor([-0.0547,  0.3098])\n",
      "\tparams: tensor([  5.0461, -15.4841])\n",
      "Epoch: 1333,Loss: 3.217986\n",
      "\tgrad: tensor([-0.0546,  0.3093])\n",
      "\tparams: tensor([  5.0466, -15.4872])\n",
      "Epoch: 1334,Loss: 3.217000\n",
      "\tgrad: tensor([-0.0545,  0.3088])\n",
      "\tparams: tensor([  5.0472, -15.4903])\n",
      "Epoch: 1335,Loss: 3.216017\n",
      "\tgrad: tensor([-0.0544,  0.3082])\n",
      "\tparams: tensor([  5.0477, -15.4934])\n",
      "Epoch: 1336,Loss: 3.215038\n",
      "\tgrad: tensor([-0.0543,  0.3077])\n",
      "\tparams: tensor([  5.0483, -15.4965])\n",
      "Epoch: 1337,Loss: 3.214062\n",
      "\tgrad: tensor([-0.0543,  0.3072])\n",
      "\tparams: tensor([  5.0488, -15.4995])\n",
      "Epoch: 1338,Loss: 3.213092\n",
      "\tgrad: tensor([-0.0542,  0.3067])\n",
      "\tparams: tensor([  5.0494, -15.5026])\n",
      "Epoch: 1339,Loss: 3.212122\n",
      "\tgrad: tensor([-0.0541,  0.3061])\n",
      "\tparams: tensor([  5.0499, -15.5057])\n",
      "Epoch: 1340,Loss: 3.211157\n",
      "\tgrad: tensor([-0.0540,  0.3056])\n",
      "\tparams: tensor([  5.0504, -15.5087])\n",
      "Epoch: 1341,Loss: 3.210192\n",
      "\tgrad: tensor([-0.0539,  0.3051])\n",
      "\tparams: tensor([  5.0510, -15.5118])\n",
      "Epoch: 1342,Loss: 3.209235\n",
      "\tgrad: tensor([-0.0538,  0.3046])\n",
      "\tparams: tensor([  5.0515, -15.5148])\n",
      "Epoch: 1343,Loss: 3.208279\n",
      "\tgrad: tensor([-0.0537,  0.3041])\n",
      "\tparams: tensor([  5.0521, -15.5179])\n",
      "Epoch: 1344,Loss: 3.207326\n",
      "\tgrad: tensor([-0.0536,  0.3036])\n",
      "\tparams: tensor([  5.0526, -15.5209])\n",
      "Epoch: 1345,Loss: 3.206376\n",
      "\tgrad: tensor([-0.0535,  0.3030])\n",
      "\tparams: tensor([  5.0531, -15.5239])\n",
      "Epoch: 1346,Loss: 3.205430\n",
      "\tgrad: tensor([-0.0534,  0.3025])\n",
      "\tparams: tensor([  5.0537, -15.5269])\n",
      "Epoch: 1347,Loss: 3.204488\n",
      "\tgrad: tensor([-0.0533,  0.3020])\n",
      "\tparams: tensor([  5.0542, -15.5300])\n",
      "Epoch: 1348,Loss: 3.203547\n",
      "\tgrad: tensor([-0.0532,  0.3015])\n",
      "\tparams: tensor([  5.0547, -15.5330])\n",
      "Epoch: 1349,Loss: 3.202610\n",
      "\tgrad: tensor([-0.0532,  0.3010])\n",
      "\tparams: tensor([  5.0553, -15.5360])\n",
      "Epoch: 1350,Loss: 3.201678\n",
      "\tgrad: tensor([-0.0531,  0.3005])\n",
      "\tparams: tensor([  5.0558, -15.5390])\n",
      "Epoch: 1351,Loss: 3.200747\n",
      "\tgrad: tensor([-0.0530,  0.3000])\n",
      "\tparams: tensor([  5.0563, -15.5420])\n",
      "Epoch: 1352,Loss: 3.199820\n",
      "\tgrad: tensor([-0.0529,  0.2995])\n",
      "\tparams: tensor([  5.0568, -15.5450])\n",
      "Epoch: 1353,Loss: 3.198897\n",
      "\tgrad: tensor([-0.0528,  0.2989])\n",
      "\tparams: tensor([  5.0574, -15.5480])\n",
      "Epoch: 1354,Loss: 3.197976\n",
      "\tgrad: tensor([-0.0527,  0.2984])\n",
      "\tparams: tensor([  5.0579, -15.5510])\n",
      "Epoch: 1355,Loss: 3.197060\n",
      "\tgrad: tensor([-0.0526,  0.2979])\n",
      "\tparams: tensor([  5.0584, -15.5539])\n",
      "Epoch: 1356,Loss: 3.196143\n",
      "\tgrad: tensor([-0.0525,  0.2974])\n",
      "\tparams: tensor([  5.0590, -15.5569])\n",
      "Epoch: 1357,Loss: 3.195231\n",
      "\tgrad: tensor([-0.0524,  0.2969])\n",
      "\tparams: tensor([  5.0595, -15.5599])\n",
      "Epoch: 1358,Loss: 3.194324\n",
      "\tgrad: tensor([-0.0524,  0.2964])\n",
      "\tparams: tensor([  5.0600, -15.5629])\n",
      "Epoch: 1359,Loss: 3.193420\n",
      "\tgrad: tensor([-0.0523,  0.2959])\n",
      "\tparams: tensor([  5.0605, -15.5658])\n",
      "Epoch: 1360,Loss: 3.192517\n",
      "\tgrad: tensor([-0.0522,  0.2954])\n",
      "\tparams: tensor([  5.0610, -15.5688])\n",
      "Epoch: 1361,Loss: 3.191616\n",
      "\tgrad: tensor([-0.0521,  0.2949])\n",
      "\tparams: tensor([  5.0616, -15.5717])\n",
      "Epoch: 1362,Loss: 3.190720\n",
      "\tgrad: tensor([-0.0520,  0.2944])\n",
      "\tparams: tensor([  5.0621, -15.5747])\n",
      "Epoch: 1363,Loss: 3.189829\n",
      "\tgrad: tensor([-0.0519,  0.2939])\n",
      "\tparams: tensor([  5.0626, -15.5776])\n",
      "Epoch: 1364,Loss: 3.188938\n",
      "\tgrad: tensor([-0.0518,  0.2934])\n",
      "\tparams: tensor([  5.0631, -15.5805])\n",
      "Epoch: 1365,Loss: 3.188051\n",
      "\tgrad: tensor([-0.0517,  0.2929])\n",
      "\tparams: tensor([  5.0636, -15.5835])\n",
      "Epoch: 1366,Loss: 3.187166\n",
      "\tgrad: tensor([-0.0516,  0.2924])\n",
      "\tparams: tensor([  5.0642, -15.5864])\n",
      "Epoch: 1367,Loss: 3.186287\n",
      "\tgrad: tensor([-0.0516,  0.2919])\n",
      "\tparams: tensor([  5.0647, -15.5893])\n",
      "Epoch: 1368,Loss: 3.185409\n",
      "\tgrad: tensor([-0.0515,  0.2914])\n",
      "\tparams: tensor([  5.0652, -15.5922])\n",
      "Epoch: 1369,Loss: 3.184534\n",
      "\tgrad: tensor([-0.0514,  0.2909])\n",
      "\tparams: tensor([  5.0657, -15.5951])\n",
      "Epoch: 1370,Loss: 3.183662\n",
      "\tgrad: tensor([-0.0513,  0.2904])\n",
      "\tparams: tensor([  5.0662, -15.5980])\n",
      "Epoch: 1371,Loss: 3.182792\n",
      "\tgrad: tensor([-0.0512,  0.2899])\n",
      "\tparams: tensor([  5.0667, -15.6009])\n",
      "Epoch: 1372,Loss: 3.181925\n",
      "\tgrad: tensor([-0.0511,  0.2894])\n",
      "\tparams: tensor([  5.0672, -15.6038])\n",
      "Epoch: 1373,Loss: 3.181063\n",
      "\tgrad: tensor([-0.0510,  0.2890])\n",
      "\tparams: tensor([  5.0678, -15.6067])\n",
      "Epoch: 1374,Loss: 3.180201\n",
      "\tgrad: tensor([-0.0509,  0.2885])\n",
      "\tparams: tensor([  5.0683, -15.6096])\n",
      "Epoch: 1375,Loss: 3.179347\n",
      "\tgrad: tensor([-0.0509,  0.2880])\n",
      "\tparams: tensor([  5.0688, -15.6125])\n",
      "Epoch: 1376,Loss: 3.178490\n",
      "\tgrad: tensor([-0.0508,  0.2875])\n",
      "\tparams: tensor([  5.0693, -15.6154])\n",
      "Epoch: 1377,Loss: 3.177638\n",
      "\tgrad: tensor([-0.0507,  0.2870])\n",
      "\tparams: tensor([  5.0698, -15.6182])\n",
      "Epoch: 1378,Loss: 3.176789\n",
      "\tgrad: tensor([-0.0506,  0.2865])\n",
      "\tparams: tensor([  5.0703, -15.6211])\n",
      "Epoch: 1379,Loss: 3.175945\n",
      "\tgrad: tensor([-0.0505,  0.2860])\n",
      "\tparams: tensor([  5.0708, -15.6240])\n",
      "Epoch: 1380,Loss: 3.175101\n",
      "\tgrad: tensor([-0.0504,  0.2855])\n",
      "\tparams: tensor([  5.0713, -15.6268])\n",
      "Epoch: 1381,Loss: 3.174262\n",
      "\tgrad: tensor([-0.0504,  0.2850])\n",
      "\tparams: tensor([  5.0718, -15.6297])\n",
      "Epoch: 1382,Loss: 3.173425\n",
      "\tgrad: tensor([-0.0503,  0.2846])\n",
      "\tparams: tensor([  5.0723, -15.6325])\n",
      "Epoch: 1383,Loss: 3.172590\n",
      "\tgrad: tensor([-0.0502,  0.2841])\n",
      "\tparams: tensor([  5.0728, -15.6353])\n",
      "Epoch: 1384,Loss: 3.171759\n",
      "\tgrad: tensor([-0.0501,  0.2836])\n",
      "\tparams: tensor([  5.0733, -15.6382])\n",
      "Epoch: 1385,Loss: 3.170929\n",
      "\tgrad: tensor([-0.0500,  0.2831])\n",
      "\tparams: tensor([  5.0738, -15.6410])\n",
      "Epoch: 1386,Loss: 3.170103\n",
      "\tgrad: tensor([-0.0499,  0.2826])\n",
      "\tparams: tensor([  5.0743, -15.6438])\n",
      "Epoch: 1387,Loss: 3.169280\n",
      "\tgrad: tensor([-0.0498,  0.2822])\n",
      "\tparams: tensor([  5.0748, -15.6467])\n",
      "Epoch: 1388,Loss: 3.168462\n",
      "\tgrad: tensor([-0.0498,  0.2817])\n",
      "\tparams: tensor([  5.0753, -15.6495])\n",
      "Epoch: 1389,Loss: 3.167644\n",
      "\tgrad: tensor([-0.0497,  0.2812])\n",
      "\tparams: tensor([  5.0758, -15.6523])\n",
      "Epoch: 1390,Loss: 3.166827\n",
      "\tgrad: tensor([-0.0496,  0.2807])\n",
      "\tparams: tensor([  5.0763, -15.6551])\n",
      "Epoch: 1391,Loss: 3.166017\n",
      "\tgrad: tensor([-0.0495,  0.2802])\n",
      "\tparams: tensor([  5.0768, -15.6579])\n",
      "Epoch: 1392,Loss: 3.165207\n",
      "\tgrad: tensor([-0.0494,  0.2798])\n",
      "\tparams: tensor([  5.0773, -15.6607])\n",
      "Epoch: 1393,Loss: 3.164401\n",
      "\tgrad: tensor([-0.0493,  0.2793])\n",
      "\tparams: tensor([  5.0778, -15.6635])\n",
      "Epoch: 1394,Loss: 3.163594\n",
      "\tgrad: tensor([-0.0492,  0.2788])\n",
      "\tparams: tensor([  5.0783, -15.6663])\n",
      "Epoch: 1395,Loss: 3.162795\n",
      "\tgrad: tensor([-0.0492,  0.2783])\n",
      "\tparams: tensor([  5.0788, -15.6691])\n",
      "Epoch: 1396,Loss: 3.161996\n",
      "\tgrad: tensor([-0.0491,  0.2779])\n",
      "\tparams: tensor([  5.0793, -15.6718])\n",
      "Epoch: 1397,Loss: 3.161201\n",
      "\tgrad: tensor([-0.0490,  0.2774])\n",
      "\tparams: tensor([  5.0797, -15.6746])\n",
      "Epoch: 1398,Loss: 3.160410\n",
      "\tgrad: tensor([-0.0489,  0.2769])\n",
      "\tparams: tensor([  5.0802, -15.6774])\n",
      "Epoch: 1399,Loss: 3.159618\n",
      "\tgrad: tensor([-0.0488,  0.2765])\n",
      "\tparams: tensor([  5.0807, -15.6802])\n",
      "Epoch: 1400,Loss: 3.158830\n",
      "\tgrad: tensor([-0.0488,  0.2760])\n",
      "\tparams: tensor([  5.0812, -15.6829])\n",
      "Epoch: 1401,Loss: 3.158046\n",
      "\tgrad: tensor([-0.0487,  0.2755])\n",
      "\tparams: tensor([  5.0817, -15.6857])\n",
      "Epoch: 1402,Loss: 3.157263\n",
      "\tgrad: tensor([-0.0486,  0.2751])\n",
      "\tparams: tensor([  5.0822, -15.6884])\n",
      "Epoch: 1403,Loss: 3.156484\n",
      "\tgrad: tensor([-0.0485,  0.2746])\n",
      "\tparams: tensor([  5.0827, -15.6912])\n",
      "Epoch: 1404,Loss: 3.155708\n",
      "\tgrad: tensor([-0.0484,  0.2741])\n",
      "\tparams: tensor([  5.0832, -15.6939])\n",
      "Epoch: 1405,Loss: 3.154933\n",
      "\tgrad: tensor([-0.0483,  0.2736])\n",
      "\tparams: tensor([  5.0836, -15.6966])\n",
      "Epoch: 1406,Loss: 3.154162\n",
      "\tgrad: tensor([-0.0483,  0.2732])\n",
      "\tparams: tensor([  5.0841, -15.6994])\n",
      "Epoch: 1407,Loss: 3.153393\n",
      "\tgrad: tensor([-0.0482,  0.2727])\n",
      "\tparams: tensor([  5.0846, -15.7021])\n",
      "Epoch: 1408,Loss: 3.152628\n",
      "\tgrad: tensor([-0.0481,  0.2723])\n",
      "\tparams: tensor([  5.0851, -15.7048])\n",
      "Epoch: 1409,Loss: 3.151865\n",
      "\tgrad: tensor([-0.0480,  0.2718])\n",
      "\tparams: tensor([  5.0856, -15.7075])\n",
      "Epoch: 1410,Loss: 3.151101\n",
      "\tgrad: tensor([-0.0479,  0.2713])\n",
      "\tparams: tensor([  5.0860, -15.7103])\n",
      "Epoch: 1411,Loss: 3.150343\n",
      "\tgrad: tensor([-0.0479,  0.2709])\n",
      "\tparams: tensor([  5.0865, -15.7130])\n",
      "Epoch: 1412,Loss: 3.149587\n",
      "\tgrad: tensor([-0.0478,  0.2704])\n",
      "\tparams: tensor([  5.0870, -15.7157])\n",
      "Epoch: 1413,Loss: 3.148833\n",
      "\tgrad: tensor([-0.0477,  0.2700])\n",
      "\tparams: tensor([  5.0875, -15.7184])\n",
      "Epoch: 1414,Loss: 3.148083\n",
      "\tgrad: tensor([-0.0476,  0.2695])\n",
      "\tparams: tensor([  5.0879, -15.7211])\n",
      "Epoch: 1415,Loss: 3.147335\n",
      "\tgrad: tensor([-0.0475,  0.2690])\n",
      "\tparams: tensor([  5.0884, -15.7238])\n",
      "Epoch: 1416,Loss: 3.146588\n",
      "\tgrad: tensor([-0.0474,  0.2686])\n",
      "\tparams: tensor([  5.0889, -15.7264])\n",
      "Epoch: 1417,Loss: 3.145845\n",
      "\tgrad: tensor([-0.0474,  0.2681])\n",
      "\tparams: tensor([  5.0894, -15.7291])\n",
      "Epoch: 1418,Loss: 3.145105\n",
      "\tgrad: tensor([-0.0473,  0.2677])\n",
      "\tparams: tensor([  5.0898, -15.7318])\n",
      "Epoch: 1419,Loss: 3.144367\n",
      "\tgrad: tensor([-0.0472,  0.2672])\n",
      "\tparams: tensor([  5.0903, -15.7345])\n",
      "Epoch: 1420,Loss: 3.143630\n",
      "\tgrad: tensor([-0.0471,  0.2668])\n",
      "\tparams: tensor([  5.0908, -15.7371])\n",
      "Epoch: 1421,Loss: 3.142899\n",
      "\tgrad: tensor([-0.0470,  0.2663])\n",
      "\tparams: tensor([  5.0913, -15.7398])\n",
      "Epoch: 1422,Loss: 3.142166\n",
      "\tgrad: tensor([-0.0469,  0.2659])\n",
      "\tparams: tensor([  5.0917, -15.7425])\n",
      "Epoch: 1423,Loss: 3.141439\n",
      "\tgrad: tensor([-0.0469,  0.2654])\n",
      "\tparams: tensor([  5.0922, -15.7451])\n",
      "Epoch: 1424,Loss: 3.140712\n",
      "\tgrad: tensor([-0.0468,  0.2649])\n",
      "\tparams: tensor([  5.0927, -15.7478])\n",
      "Epoch: 1425,Loss: 3.139989\n",
      "\tgrad: tensor([-0.0467,  0.2645])\n",
      "\tparams: tensor([  5.0931, -15.7504])\n",
      "Epoch: 1426,Loss: 3.139271\n",
      "\tgrad: tensor([-0.0466,  0.2641])\n",
      "\tparams: tensor([  5.0936, -15.7530])\n",
      "Epoch: 1427,Loss: 3.138551\n",
      "\tgrad: tensor([-0.0466,  0.2636])\n",
      "\tparams: tensor([  5.0941, -15.7557])\n",
      "Epoch: 1428,Loss: 3.137835\n",
      "\tgrad: tensor([-0.0465,  0.2632])\n",
      "\tparams: tensor([  5.0945, -15.7583])\n",
      "Epoch: 1429,Loss: 3.137121\n",
      "\tgrad: tensor([-0.0464,  0.2627])\n",
      "\tparams: tensor([  5.0950, -15.7609])\n",
      "Epoch: 1430,Loss: 3.136409\n",
      "\tgrad: tensor([-0.0463,  0.2623])\n",
      "\tparams: tensor([  5.0955, -15.7636])\n",
      "Epoch: 1431,Loss: 3.135702\n",
      "\tgrad: tensor([-0.0462,  0.2618])\n",
      "\tparams: tensor([  5.0959, -15.7662])\n",
      "Epoch: 1432,Loss: 3.134994\n",
      "\tgrad: tensor([-0.0461,  0.2614])\n",
      "\tparams: tensor([  5.0964, -15.7688])\n",
      "Epoch: 1433,Loss: 3.134292\n",
      "\tgrad: tensor([-0.0461,  0.2609])\n",
      "\tparams: tensor([  5.0968, -15.7714])\n",
      "Epoch: 1434,Loss: 3.133590\n",
      "\tgrad: tensor([-0.0460,  0.2605])\n",
      "\tparams: tensor([  5.0973, -15.7740])\n",
      "Epoch: 1435,Loss: 3.132889\n",
      "\tgrad: tensor([-0.0459,  0.2600])\n",
      "\tparams: tensor([  5.0978, -15.7766])\n",
      "Epoch: 1436,Loss: 3.132194\n",
      "\tgrad: tensor([-0.0459,  0.2596])\n",
      "\tparams: tensor([  5.0982, -15.7792])\n",
      "Epoch: 1437,Loss: 3.131500\n",
      "\tgrad: tensor([-0.0458,  0.2592])\n",
      "\tparams: tensor([  5.0987, -15.7818])\n",
      "Epoch: 1438,Loss: 3.130810\n",
      "\tgrad: tensor([-0.0457,  0.2587])\n",
      "\tparams: tensor([  5.0991, -15.7844])\n",
      "Epoch: 1439,Loss: 3.130119\n",
      "\tgrad: tensor([-0.0456,  0.2583])\n",
      "\tparams: tensor([  5.0996, -15.7870])\n",
      "Epoch: 1440,Loss: 3.129432\n",
      "\tgrad: tensor([-0.0455,  0.2578])\n",
      "\tparams: tensor([  5.1000, -15.7895])\n",
      "Epoch: 1441,Loss: 3.128746\n",
      "\tgrad: tensor([-0.0455,  0.2574])\n",
      "\tparams: tensor([  5.1005, -15.7921])\n",
      "Epoch: 1442,Loss: 3.128064\n",
      "\tgrad: tensor([-0.0454,  0.2570])\n",
      "\tparams: tensor([  5.1010, -15.7947])\n",
      "Epoch: 1443,Loss: 3.127382\n",
      "\tgrad: tensor([-0.0453,  0.2565])\n",
      "\tparams: tensor([  5.1014, -15.7973])\n",
      "Epoch: 1444,Loss: 3.126705\n",
      "\tgrad: tensor([-0.0453,  0.2561])\n",
      "\tparams: tensor([  5.1019, -15.7998])\n",
      "Epoch: 1445,Loss: 3.126030\n",
      "\tgrad: tensor([-0.0452,  0.2557])\n",
      "\tparams: tensor([  5.1023, -15.8024])\n",
      "Epoch: 1446,Loss: 3.125356\n",
      "\tgrad: tensor([-0.0451,  0.2552])\n",
      "\tparams: tensor([  5.1028, -15.8049])\n",
      "Epoch: 1447,Loss: 3.124683\n",
      "\tgrad: tensor([-0.0450,  0.2548])\n",
      "\tparams: tensor([  5.1032, -15.8075])\n",
      "Epoch: 1448,Loss: 3.124016\n",
      "\tgrad: tensor([-0.0449,  0.2544])\n",
      "\tparams: tensor([  5.1037, -15.8100])\n",
      "Epoch: 1449,Loss: 3.123349\n",
      "\tgrad: tensor([-0.0449,  0.2539])\n",
      "\tparams: tensor([  5.1041, -15.8126])\n",
      "Epoch: 1450,Loss: 3.122686\n",
      "\tgrad: tensor([-0.0448,  0.2535])\n",
      "\tparams: tensor([  5.1046, -15.8151])\n",
      "Epoch: 1451,Loss: 3.122022\n",
      "\tgrad: tensor([-0.0447,  0.2531])\n",
      "\tparams: tensor([  5.1050, -15.8176])\n",
      "Epoch: 1452,Loss: 3.121362\n",
      "\tgrad: tensor([-0.0446,  0.2526])\n",
      "\tparams: tensor([  5.1055, -15.8201])\n",
      "Epoch: 1453,Loss: 3.120707\n",
      "\tgrad: tensor([-0.0445,  0.2522])\n",
      "\tparams: tensor([  5.1059, -15.8227])\n",
      "Epoch: 1454,Loss: 3.120049\n",
      "\tgrad: tensor([-0.0445,  0.2518])\n",
      "\tparams: tensor([  5.1063, -15.8252])\n",
      "Epoch: 1455,Loss: 3.119397\n",
      "\tgrad: tensor([-0.0444,  0.2513])\n",
      "\tparams: tensor([  5.1068, -15.8277])\n",
      "Epoch: 1456,Loss: 3.118746\n",
      "\tgrad: tensor([-0.0443,  0.2509])\n",
      "\tparams: tensor([  5.1072, -15.8302])\n",
      "Epoch: 1457,Loss: 3.118098\n",
      "\tgrad: tensor([-0.0442,  0.2505])\n",
      "\tparams: tensor([  5.1077, -15.8327])\n",
      "Epoch: 1458,Loss: 3.117451\n",
      "\tgrad: tensor([-0.0442,  0.2501])\n",
      "\tparams: tensor([  5.1081, -15.8352])\n",
      "Epoch: 1459,Loss: 3.116805\n",
      "\tgrad: tensor([-0.0441,  0.2496])\n",
      "\tparams: tensor([  5.1086, -15.8377])\n",
      "Epoch: 1460,Loss: 3.116164\n",
      "\tgrad: tensor([-0.0440,  0.2492])\n",
      "\tparams: tensor([  5.1090, -15.8402])\n",
      "Epoch: 1461,Loss: 3.115525\n",
      "\tgrad: tensor([-0.0439,  0.2488])\n",
      "\tparams: tensor([  5.1094, -15.8427])\n",
      "Epoch: 1462,Loss: 3.114886\n",
      "\tgrad: tensor([-0.0439,  0.2484])\n",
      "\tparams: tensor([  5.1099, -15.8452])\n",
      "Epoch: 1463,Loss: 3.114251\n",
      "\tgrad: tensor([-0.0438,  0.2480])\n",
      "\tparams: tensor([  5.1103, -15.8477])\n",
      "Epoch: 1464,Loss: 3.113617\n",
      "\tgrad: tensor([-0.0437,  0.2475])\n",
      "\tparams: tensor([  5.1107, -15.8501])\n",
      "Epoch: 1465,Loss: 3.112985\n",
      "\tgrad: tensor([-0.0437,  0.2471])\n",
      "\tparams: tensor([  5.1112, -15.8526])\n",
      "Epoch: 1466,Loss: 3.112358\n",
      "\tgrad: tensor([-0.0436,  0.2467])\n",
      "\tparams: tensor([  5.1116, -15.8551])\n",
      "Epoch: 1467,Loss: 3.111731\n",
      "\tgrad: tensor([-0.0435,  0.2463])\n",
      "\tparams: tensor([  5.1121, -15.8575])\n",
      "Epoch: 1468,Loss: 3.111103\n",
      "\tgrad: tensor([-0.0434,  0.2459])\n",
      "\tparams: tensor([  5.1125, -15.8600])\n",
      "Epoch: 1469,Loss: 3.110484\n",
      "\tgrad: tensor([-0.0433,  0.2454])\n",
      "\tparams: tensor([  5.1129, -15.8624])\n",
      "Epoch: 1470,Loss: 3.109859\n",
      "\tgrad: tensor([-0.0433,  0.2450])\n",
      "\tparams: tensor([  5.1134, -15.8649])\n",
      "Epoch: 1471,Loss: 3.109243\n",
      "\tgrad: tensor([-0.0432,  0.2446])\n",
      "\tparams: tensor([  5.1138, -15.8673])\n",
      "Epoch: 1472,Loss: 3.108627\n",
      "\tgrad: tensor([-0.0431,  0.2442])\n",
      "\tparams: tensor([  5.1142, -15.8698])\n",
      "Epoch: 1473,Loss: 3.108011\n",
      "\tgrad: tensor([-0.0430,  0.2438])\n",
      "\tparams: tensor([  5.1147, -15.8722])\n",
      "Epoch: 1474,Loss: 3.107401\n",
      "\tgrad: tensor([-0.0430,  0.2434])\n",
      "\tparams: tensor([  5.1151, -15.8747])\n",
      "Epoch: 1475,Loss: 3.106791\n",
      "\tgrad: tensor([-0.0429,  0.2429])\n",
      "\tparams: tensor([  5.1155, -15.8771])\n",
      "Epoch: 1476,Loss: 3.106180\n",
      "\tgrad: tensor([-0.0428,  0.2425])\n",
      "\tparams: tensor([  5.1159, -15.8795])\n",
      "Epoch: 1477,Loss: 3.105575\n",
      "\tgrad: tensor([-0.0428,  0.2421])\n",
      "\tparams: tensor([  5.1164, -15.8819])\n",
      "Epoch: 1478,Loss: 3.104972\n",
      "\tgrad: tensor([-0.0427,  0.2417])\n",
      "\tparams: tensor([  5.1168, -15.8843])\n",
      "Epoch: 1479,Loss: 3.104370\n",
      "\tgrad: tensor([-0.0426,  0.2413])\n",
      "\tparams: tensor([  5.1172, -15.8868])\n",
      "Epoch: 1480,Loss: 3.103770\n",
      "\tgrad: tensor([-0.0425,  0.2409])\n",
      "\tparams: tensor([  5.1176, -15.8892])\n",
      "Epoch: 1481,Loss: 3.103172\n",
      "\tgrad: tensor([-0.0425,  0.2405])\n",
      "\tparams: tensor([  5.1181, -15.8916])\n",
      "Epoch: 1482,Loss: 3.102576\n",
      "\tgrad: tensor([-0.0424,  0.2401])\n",
      "\tparams: tensor([  5.1185, -15.8940])\n",
      "Epoch: 1483,Loss: 3.101982\n",
      "\tgrad: tensor([-0.0423,  0.2397])\n",
      "\tparams: tensor([  5.1189, -15.8964])\n",
      "Epoch: 1484,Loss: 3.101390\n",
      "\tgrad: tensor([-0.0423,  0.2393])\n",
      "\tparams: tensor([  5.1193, -15.8988])\n",
      "Epoch: 1485,Loss: 3.100802\n",
      "\tgrad: tensor([-0.0422,  0.2388])\n",
      "\tparams: tensor([  5.1198, -15.9011])\n",
      "Epoch: 1486,Loss: 3.100213\n",
      "\tgrad: tensor([-0.0421,  0.2384])\n",
      "\tparams: tensor([  5.1202, -15.9035])\n",
      "Epoch: 1487,Loss: 3.099627\n",
      "\tgrad: tensor([-0.0421,  0.2380])\n",
      "\tparams: tensor([  5.1206, -15.9059])\n",
      "Epoch: 1488,Loss: 3.099044\n",
      "\tgrad: tensor([-0.0420,  0.2376])\n",
      "\tparams: tensor([  5.1210, -15.9083])\n",
      "Epoch: 1489,Loss: 3.098463\n",
      "\tgrad: tensor([-0.0419,  0.2372])\n",
      "\tparams: tensor([  5.1214, -15.9107])\n",
      "Epoch: 1490,Loss: 3.097883\n",
      "\tgrad: tensor([-0.0418,  0.2368])\n",
      "\tparams: tensor([  5.1219, -15.9130])\n",
      "Epoch: 1491,Loss: 3.097302\n",
      "\tgrad: tensor([-0.0418,  0.2364])\n",
      "\tparams: tensor([  5.1223, -15.9154])\n",
      "Epoch: 1492,Loss: 3.096727\n",
      "\tgrad: tensor([-0.0417,  0.2360])\n",
      "\tparams: tensor([  5.1227, -15.9178])\n",
      "Epoch: 1493,Loss: 3.096153\n",
      "\tgrad: tensor([-0.0416,  0.2356])\n",
      "\tparams: tensor([  5.1231, -15.9201])\n",
      "Epoch: 1494,Loss: 3.095583\n",
      "\tgrad: tensor([-0.0416,  0.2352])\n",
      "\tparams: tensor([  5.1235, -15.9225])\n",
      "Epoch: 1495,Loss: 3.095011\n",
      "\tgrad: tensor([-0.0415,  0.2348])\n",
      "\tparams: tensor([  5.1239, -15.9248])\n",
      "Epoch: 1496,Loss: 3.094444\n",
      "\tgrad: tensor([-0.0414,  0.2344])\n",
      "\tparams: tensor([  5.1244, -15.9272])\n",
      "Epoch: 1497,Loss: 3.093877\n",
      "\tgrad: tensor([-0.0413,  0.2340])\n",
      "\tparams: tensor([  5.1248, -15.9295])\n",
      "Epoch: 1498,Loss: 3.093314\n",
      "\tgrad: tensor([-0.0413,  0.2336])\n",
      "\tparams: tensor([  5.1252, -15.9318])\n",
      "Epoch: 1499,Loss: 3.092751\n",
      "\tgrad: tensor([-0.0412,  0.2332])\n",
      "\tparams: tensor([  5.1256, -15.9342])\n",
      "Epoch: 1500,Loss: 3.092191\n",
      "\tgrad: tensor([-0.0411,  0.2328])\n",
      "\tparams: tensor([  5.1260, -15.9365])\n",
      "Epoch: 1501,Loss: 3.091630\n",
      "\tgrad: tensor([-0.0411,  0.2324])\n",
      "\tparams: tensor([  5.1264, -15.9388])\n",
      "Epoch: 1502,Loss: 3.091074\n",
      "\tgrad: tensor([-0.0410,  0.2320])\n",
      "\tparams: tensor([  5.1268, -15.9411])\n",
      "Epoch: 1503,Loss: 3.090520\n",
      "\tgrad: tensor([-0.0409,  0.2317])\n",
      "\tparams: tensor([  5.1272, -15.9435])\n",
      "Epoch: 1504,Loss: 3.089969\n",
      "\tgrad: tensor([-0.0408,  0.2313])\n",
      "\tparams: tensor([  5.1276, -15.9458])\n",
      "Epoch: 1505,Loss: 3.089417\n",
      "\tgrad: tensor([-0.0408,  0.2309])\n",
      "\tparams: tensor([  5.1281, -15.9481])\n",
      "Epoch: 1506,Loss: 3.088867\n",
      "\tgrad: tensor([-0.0407,  0.2305])\n",
      "\tparams: tensor([  5.1285, -15.9504])\n",
      "Epoch: 1507,Loss: 3.088320\n",
      "\tgrad: tensor([-0.0406,  0.2301])\n",
      "\tparams: tensor([  5.1289, -15.9527])\n",
      "Epoch: 1508,Loss: 3.087775\n",
      "\tgrad: tensor([-0.0406,  0.2297])\n",
      "\tparams: tensor([  5.1293, -15.9550])\n",
      "Epoch: 1509,Loss: 3.087232\n",
      "\tgrad: tensor([-0.0405,  0.2293])\n",
      "\tparams: tensor([  5.1297, -15.9573])\n",
      "Epoch: 1510,Loss: 3.086690\n",
      "\tgrad: tensor([-0.0404,  0.2289])\n",
      "\tparams: tensor([  5.1301, -15.9596])\n",
      "Epoch: 1511,Loss: 3.086150\n",
      "\tgrad: tensor([-0.0404,  0.2285])\n",
      "\tparams: tensor([  5.1305, -15.9618])\n",
      "Epoch: 1512,Loss: 3.085612\n",
      "\tgrad: tensor([-0.0403,  0.2281])\n",
      "\tparams: tensor([  5.1309, -15.9641])\n",
      "Epoch: 1513,Loss: 3.085075\n",
      "\tgrad: tensor([-0.0402,  0.2277])\n",
      "\tparams: tensor([  5.1313, -15.9664])\n",
      "Epoch: 1514,Loss: 3.084542\n",
      "\tgrad: tensor([-0.0402,  0.2274])\n",
      "\tparams: tensor([  5.1317, -15.9687])\n",
      "Epoch: 1515,Loss: 3.084009\n",
      "\tgrad: tensor([-0.0401,  0.2270])\n",
      "\tparams: tensor([  5.1321, -15.9709])\n",
      "Epoch: 1516,Loss: 3.083478\n",
      "\tgrad: tensor([-0.0400,  0.2266])\n",
      "\tparams: tensor([  5.1325, -15.9732])\n",
      "Epoch: 1517,Loss: 3.082948\n",
      "\tgrad: tensor([-0.0400,  0.2262])\n",
      "\tparams: tensor([  5.1329, -15.9755])\n",
      "Epoch: 1518,Loss: 3.082422\n",
      "\tgrad: tensor([-0.0399,  0.2258])\n",
      "\tparams: tensor([  5.1333, -15.9777])\n",
      "Epoch: 1519,Loss: 3.081897\n",
      "\tgrad: tensor([-0.0398,  0.2254])\n",
      "\tparams: tensor([  5.1337, -15.9800])\n",
      "Epoch: 1520,Loss: 3.081373\n",
      "\tgrad: tensor([-0.0398,  0.2250])\n",
      "\tparams: tensor([  5.1341, -15.9822])\n",
      "Epoch: 1521,Loss: 3.080850\n",
      "\tgrad: tensor([-0.0397,  0.2247])\n",
      "\tparams: tensor([  5.1345, -15.9845])\n",
      "Epoch: 1522,Loss: 3.080331\n",
      "\tgrad: tensor([-0.0396,  0.2243])\n",
      "\tparams: tensor([  5.1349, -15.9867])\n",
      "Epoch: 1523,Loss: 3.079811\n",
      "\tgrad: tensor([-0.0396,  0.2239])\n",
      "\tparams: tensor([  5.1353, -15.9890])\n",
      "Epoch: 1524,Loss: 3.079296\n",
      "\tgrad: tensor([-0.0395,  0.2235])\n",
      "\tparams: tensor([  5.1357, -15.9912])\n",
      "Epoch: 1525,Loss: 3.078781\n",
      "\tgrad: tensor([-0.0394,  0.2231])\n",
      "\tparams: tensor([  5.1361, -15.9934])\n",
      "Epoch: 1526,Loss: 3.078268\n",
      "\tgrad: tensor([-0.0394,  0.2228])\n",
      "\tparams: tensor([  5.1365, -15.9957])\n",
      "Epoch: 1527,Loss: 3.077758\n",
      "\tgrad: tensor([-0.0393,  0.2224])\n",
      "\tparams: tensor([  5.1369, -15.9979])\n",
      "Epoch: 1528,Loss: 3.077248\n",
      "\tgrad: tensor([-0.0392,  0.2220])\n",
      "\tparams: tensor([  5.1372, -16.0001])\n",
      "Epoch: 1529,Loss: 3.076739\n",
      "\tgrad: tensor([-0.0391,  0.2216])\n",
      "\tparams: tensor([  5.1376, -16.0023])\n",
      "Epoch: 1530,Loss: 3.076232\n",
      "\tgrad: tensor([-0.0391,  0.2213])\n",
      "\tparams: tensor([  5.1380, -16.0045])\n",
      "Epoch: 1531,Loss: 3.075729\n",
      "\tgrad: tensor([-0.0390,  0.2209])\n",
      "\tparams: tensor([  5.1384, -16.0067])\n",
      "Epoch: 1532,Loss: 3.075225\n",
      "\tgrad: tensor([-0.0390,  0.2205])\n",
      "\tparams: tensor([  5.1388, -16.0089])\n",
      "Epoch: 1533,Loss: 3.074724\n",
      "\tgrad: tensor([-0.0389,  0.2201])\n",
      "\tparams: tensor([  5.1392, -16.0111])\n",
      "Epoch: 1534,Loss: 3.074227\n",
      "\tgrad: tensor([-0.0388,  0.2198])\n",
      "\tparams: tensor([  5.1396, -16.0133])\n",
      "Epoch: 1535,Loss: 3.073726\n",
      "\tgrad: tensor([-0.0387,  0.2194])\n",
      "\tparams: tensor([  5.1400, -16.0155])\n",
      "Epoch: 1536,Loss: 3.073232\n",
      "\tgrad: tensor([-0.0387,  0.2190])\n",
      "\tparams: tensor([  5.1404, -16.0177])\n",
      "Epoch: 1537,Loss: 3.072739\n",
      "\tgrad: tensor([-0.0386,  0.2186])\n",
      "\tparams: tensor([  5.1407, -16.0199])\n",
      "Epoch: 1538,Loss: 3.072245\n",
      "\tgrad: tensor([-0.0385,  0.2183])\n",
      "\tparams: tensor([  5.1411, -16.0221])\n",
      "Epoch: 1539,Loss: 3.071753\n",
      "\tgrad: tensor([-0.0385,  0.2179])\n",
      "\tparams: tensor([  5.1415, -16.0243])\n",
      "Epoch: 1540,Loss: 3.071265\n",
      "\tgrad: tensor([-0.0384,  0.2175])\n",
      "\tparams: tensor([  5.1419, -16.0264])\n",
      "Epoch: 1541,Loss: 3.070778\n",
      "\tgrad: tensor([-0.0383,  0.2172])\n",
      "\tparams: tensor([  5.1423, -16.0286])\n",
      "Epoch: 1542,Loss: 3.070293\n",
      "\tgrad: tensor([-0.0383,  0.2168])\n",
      "\tparams: tensor([  5.1427, -16.0308])\n",
      "Epoch: 1543,Loss: 3.069808\n",
      "\tgrad: tensor([-0.0382,  0.2164])\n",
      "\tparams: tensor([  5.1430, -16.0330])\n",
      "Epoch: 1544,Loss: 3.069326\n",
      "\tgrad: tensor([-0.0382,  0.2161])\n",
      "\tparams: tensor([  5.1434, -16.0351])\n",
      "Epoch: 1545,Loss: 3.068845\n",
      "\tgrad: tensor([-0.0381,  0.2157])\n",
      "\tparams: tensor([  5.1438, -16.0373])\n",
      "Epoch: 1546,Loss: 3.068366\n",
      "\tgrad: tensor([-0.0380,  0.2153])\n",
      "\tparams: tensor([  5.1442, -16.0394])\n",
      "Epoch: 1547,Loss: 3.067887\n",
      "\tgrad: tensor([-0.0380,  0.2150])\n",
      "\tparams: tensor([  5.1446, -16.0416])\n",
      "Epoch: 1548,Loss: 3.067412\n",
      "\tgrad: tensor([-0.0379,  0.2146])\n",
      "\tparams: tensor([  5.1449, -16.0437])\n",
      "Epoch: 1549,Loss: 3.066937\n",
      "\tgrad: tensor([-0.0378,  0.2142])\n",
      "\tparams: tensor([  5.1453, -16.0459])\n",
      "Epoch: 1550,Loss: 3.066463\n",
      "\tgrad: tensor([-0.0378,  0.2139])\n",
      "\tparams: tensor([  5.1457, -16.0480])\n",
      "Epoch: 1551,Loss: 3.065993\n",
      "\tgrad: tensor([-0.0377,  0.2135])\n",
      "\tparams: tensor([  5.1461, -16.0501])\n",
      "Epoch: 1552,Loss: 3.065524\n",
      "\tgrad: tensor([-0.0376,  0.2131])\n",
      "\tparams: tensor([  5.1465, -16.0523])\n",
      "Epoch: 1553,Loss: 3.065055\n",
      "\tgrad: tensor([-0.0376,  0.2128])\n",
      "\tparams: tensor([  5.1468, -16.0544])\n",
      "Epoch: 1554,Loss: 3.064588\n",
      "\tgrad: tensor([-0.0375,  0.2124])\n",
      "\tparams: tensor([  5.1472, -16.0565])\n",
      "Epoch: 1555,Loss: 3.064123\n",
      "\tgrad: tensor([-0.0375,  0.2120])\n",
      "\tparams: tensor([  5.1476, -16.0586])\n",
      "Epoch: 1556,Loss: 3.063660\n",
      "\tgrad: tensor([-0.0374,  0.2117])\n",
      "\tparams: tensor([  5.1480, -16.0608])\n",
      "Epoch: 1557,Loss: 3.063199\n",
      "\tgrad: tensor([-0.0373,  0.2113])\n",
      "\tparams: tensor([  5.1483, -16.0629])\n",
      "Epoch: 1558,Loss: 3.062738\n",
      "\tgrad: tensor([-0.0373,  0.2110])\n",
      "\tparams: tensor([  5.1487, -16.0650])\n",
      "Epoch: 1559,Loss: 3.062280\n",
      "\tgrad: tensor([-0.0372,  0.2106])\n",
      "\tparams: tensor([  5.1491, -16.0671])\n",
      "Epoch: 1560,Loss: 3.061822\n",
      "\tgrad: tensor([-0.0371,  0.2103])\n",
      "\tparams: tensor([  5.1494, -16.0692])\n",
      "Epoch: 1561,Loss: 3.061367\n",
      "\tgrad: tensor([-0.0371,  0.2099])\n",
      "\tparams: tensor([  5.1498, -16.0713])\n",
      "Epoch: 1562,Loss: 3.060913\n",
      "\tgrad: tensor([-0.0370,  0.2095])\n",
      "\tparams: tensor([  5.1502, -16.0734])\n",
      "Epoch: 1563,Loss: 3.060462\n",
      "\tgrad: tensor([-0.0370,  0.2092])\n",
      "\tparams: tensor([  5.1506, -16.0755])\n",
      "Epoch: 1564,Loss: 3.060011\n",
      "\tgrad: tensor([-0.0369,  0.2088])\n",
      "\tparams: tensor([  5.1509, -16.0776])\n",
      "Epoch: 1565,Loss: 3.059561\n",
      "\tgrad: tensor([-0.0368,  0.2085])\n",
      "\tparams: tensor([  5.1513, -16.0796])\n",
      "Epoch: 1566,Loss: 3.059114\n",
      "\tgrad: tensor([-0.0368,  0.2081])\n",
      "\tparams: tensor([  5.1517, -16.0817])\n",
      "Epoch: 1567,Loss: 3.058668\n",
      "\tgrad: tensor([-0.0367,  0.2078])\n",
      "\tparams: tensor([  5.1520, -16.0838])\n",
      "Epoch: 1568,Loss: 3.058221\n",
      "\tgrad: tensor([-0.0366,  0.2074])\n",
      "\tparams: tensor([  5.1524, -16.0859])\n",
      "Epoch: 1569,Loss: 3.057781\n",
      "\tgrad: tensor([-0.0366,  0.2071])\n",
      "\tparams: tensor([  5.1528, -16.0880])\n",
      "Epoch: 1570,Loss: 3.057338\n",
      "\tgrad: tensor([-0.0365,  0.2067])\n",
      "\tparams: tensor([  5.1531, -16.0900])\n",
      "Epoch: 1571,Loss: 3.056898\n",
      "\tgrad: tensor([-0.0364,  0.2064])\n",
      "\tparams: tensor([  5.1535, -16.0921])\n",
      "Epoch: 1572,Loss: 3.056458\n",
      "\tgrad: tensor([-0.0364,  0.2060])\n",
      "\tparams: tensor([  5.1539, -16.0941])\n",
      "Epoch: 1573,Loss: 3.056019\n",
      "\tgrad: tensor([-0.0363,  0.2057])\n",
      "\tparams: tensor([  5.1542, -16.0962])\n",
      "Epoch: 1574,Loss: 3.055585\n",
      "\tgrad: tensor([-0.0363,  0.2053])\n",
      "\tparams: tensor([  5.1546, -16.0983])\n",
      "Epoch: 1575,Loss: 3.055151\n",
      "\tgrad: tensor([-0.0362,  0.2050])\n",
      "\tparams: tensor([  5.1549, -16.1003])\n",
      "Epoch: 1576,Loss: 3.054717\n",
      "\tgrad: tensor([-0.0361,  0.2046])\n",
      "\tparams: tensor([  5.1553, -16.1023])\n",
      "Epoch: 1577,Loss: 3.054286\n",
      "\tgrad: tensor([-0.0361,  0.2043])\n",
      "\tparams: tensor([  5.1557, -16.1044])\n",
      "Epoch: 1578,Loss: 3.053857\n",
      "\tgrad: tensor([-0.0360,  0.2039])\n",
      "\tparams: tensor([  5.1560, -16.1064])\n",
      "Epoch: 1579,Loss: 3.053427\n",
      "\tgrad: tensor([-0.0360,  0.2036])\n",
      "\tparams: tensor([  5.1564, -16.1085])\n",
      "Epoch: 1580,Loss: 3.053000\n",
      "\tgrad: tensor([-0.0359,  0.2032])\n",
      "\tparams: tensor([  5.1567, -16.1105])\n",
      "Epoch: 1581,Loss: 3.052576\n",
      "\tgrad: tensor([-0.0358,  0.2029])\n",
      "\tparams: tensor([  5.1571, -16.1125])\n",
      "Epoch: 1582,Loss: 3.052152\n",
      "\tgrad: tensor([-0.0358,  0.2025])\n",
      "\tparams: tensor([  5.1575, -16.1146])\n",
      "Epoch: 1583,Loss: 3.051730\n",
      "\tgrad: tensor([-0.0357,  0.2022])\n",
      "\tparams: tensor([  5.1578, -16.1166])\n",
      "Epoch: 1584,Loss: 3.051306\n",
      "\tgrad: tensor([-0.0357,  0.2018])\n",
      "\tparams: tensor([  5.1582, -16.1186])\n",
      "Epoch: 1585,Loss: 3.050888\n",
      "\tgrad: tensor([-0.0356,  0.2015])\n",
      "\tparams: tensor([  5.1585, -16.1206])\n",
      "Epoch: 1586,Loss: 3.050471\n",
      "\tgrad: tensor([-0.0355,  0.2012])\n",
      "\tparams: tensor([  5.1589, -16.1226])\n",
      "Epoch: 1587,Loss: 3.050052\n",
      "\tgrad: tensor([-0.0355,  0.2008])\n",
      "\tparams: tensor([  5.1592, -16.1246])\n",
      "Epoch: 1588,Loss: 3.049639\n",
      "\tgrad: tensor([-0.0354,  0.2005])\n",
      "\tparams: tensor([  5.1596, -16.1266])\n",
      "Epoch: 1589,Loss: 3.049223\n",
      "\tgrad: tensor([-0.0354,  0.2001])\n",
      "\tparams: tensor([  5.1599, -16.1286])\n",
      "Epoch: 1590,Loss: 3.048811\n",
      "\tgrad: tensor([-0.0353,  0.1998])\n",
      "\tparams: tensor([  5.1603, -16.1306])\n",
      "Epoch: 1591,Loss: 3.048398\n",
      "\tgrad: tensor([-0.0353,  0.1995])\n",
      "\tparams: tensor([  5.1607, -16.1326])\n",
      "Epoch: 1592,Loss: 3.047991\n",
      "\tgrad: tensor([-0.0352,  0.1991])\n",
      "\tparams: tensor([  5.1610, -16.1346])\n",
      "Epoch: 1593,Loss: 3.047581\n",
      "\tgrad: tensor([-0.0351,  0.1988])\n",
      "\tparams: tensor([  5.1614, -16.1366])\n",
      "Epoch: 1594,Loss: 3.047173\n",
      "\tgrad: tensor([-0.0351,  0.1984])\n",
      "\tparams: tensor([  5.1617, -16.1386])\n",
      "Epoch: 1595,Loss: 3.046768\n",
      "\tgrad: tensor([-0.0350,  0.1981])\n",
      "\tparams: tensor([  5.1621, -16.1406])\n",
      "Epoch: 1596,Loss: 3.046362\n",
      "\tgrad: tensor([-0.0349,  0.1978])\n",
      "\tparams: tensor([  5.1624, -16.1425])\n",
      "Epoch: 1597,Loss: 3.045960\n",
      "\tgrad: tensor([-0.0349,  0.1974])\n",
      "\tparams: tensor([  5.1628, -16.1445])\n",
      "Epoch: 1598,Loss: 3.045559\n",
      "\tgrad: tensor([-0.0348,  0.1971])\n",
      "\tparams: tensor([  5.1631, -16.1465])\n",
      "Epoch: 1599,Loss: 3.045160\n",
      "\tgrad: tensor([-0.0348,  0.1968])\n",
      "\tparams: tensor([  5.1635, -16.1485])\n",
      "Epoch: 1600,Loss: 3.044759\n",
      "\tgrad: tensor([-0.0347,  0.1964])\n",
      "\tparams: tensor([  5.1638, -16.1504])\n",
      "Epoch: 1601,Loss: 3.044361\n",
      "\tgrad: tensor([-0.0346,  0.1961])\n",
      "\tparams: tensor([  5.1641, -16.1524])\n",
      "Epoch: 1602,Loss: 3.043966\n",
      "\tgrad: tensor([-0.0346,  0.1958])\n",
      "\tparams: tensor([  5.1645, -16.1543])\n",
      "Epoch: 1603,Loss: 3.043571\n",
      "\tgrad: tensor([-0.0345,  0.1954])\n",
      "\tparams: tensor([  5.1648, -16.1563])\n",
      "Epoch: 1604,Loss: 3.043176\n",
      "\tgrad: tensor([-0.0345,  0.1951])\n",
      "\tparams: tensor([  5.1652, -16.1582])\n",
      "Epoch: 1605,Loss: 3.042785\n",
      "\tgrad: tensor([-0.0344,  0.1948])\n",
      "\tparams: tensor([  5.1655, -16.1602])\n",
      "Epoch: 1606,Loss: 3.042395\n",
      "\tgrad: tensor([-0.0343,  0.1944])\n",
      "\tparams: tensor([  5.1659, -16.1621])\n",
      "Epoch: 1607,Loss: 3.042005\n",
      "\tgrad: tensor([-0.0343,  0.1941])\n",
      "\tparams: tensor([  5.1662, -16.1641])\n",
      "Epoch: 1608,Loss: 3.041615\n",
      "\tgrad: tensor([-0.0342,  0.1938])\n",
      "\tparams: tensor([  5.1666, -16.1660])\n",
      "Epoch: 1609,Loss: 3.041230\n",
      "\tgrad: tensor([-0.0342,  0.1934])\n",
      "\tparams: tensor([  5.1669, -16.1680])\n",
      "Epoch: 1610,Loss: 3.040844\n",
      "\tgrad: tensor([-0.0341,  0.1931])\n",
      "\tparams: tensor([  5.1672, -16.1699])\n",
      "Epoch: 1611,Loss: 3.040461\n",
      "\tgrad: tensor([-0.0341,  0.1928])\n",
      "\tparams: tensor([  5.1676, -16.1718])\n",
      "Epoch: 1612,Loss: 3.040077\n",
      "\tgrad: tensor([-0.0340,  0.1925])\n",
      "\tparams: tensor([  5.1679, -16.1737])\n",
      "Epoch: 1613,Loss: 3.039695\n",
      "\tgrad: tensor([-0.0339,  0.1921])\n",
      "\tparams: tensor([  5.1683, -16.1757])\n",
      "Epoch: 1614,Loss: 3.039314\n",
      "\tgrad: tensor([-0.0339,  0.1918])\n",
      "\tparams: tensor([  5.1686, -16.1776])\n",
      "Epoch: 1615,Loss: 3.038934\n",
      "\tgrad: tensor([-0.0338,  0.1915])\n",
      "\tparams: tensor([  5.1689, -16.1795])\n",
      "Epoch: 1616,Loss: 3.038557\n",
      "\tgrad: tensor([-0.0338,  0.1912])\n",
      "\tparams: tensor([  5.1693, -16.1814])\n",
      "Epoch: 1617,Loss: 3.038181\n",
      "\tgrad: tensor([-0.0337,  0.1908])\n",
      "\tparams: tensor([  5.1696, -16.1833])\n",
      "Epoch: 1618,Loss: 3.037805\n",
      "\tgrad: tensor([-0.0337,  0.1905])\n",
      "\tparams: tensor([  5.1699, -16.1852])\n",
      "Epoch: 1619,Loss: 3.037432\n",
      "\tgrad: tensor([-0.0336,  0.1902])\n",
      "\tparams: tensor([  5.1703, -16.1871])\n",
      "Epoch: 1620,Loss: 3.037059\n",
      "\tgrad: tensor([-0.0335,  0.1899])\n",
      "\tparams: tensor([  5.1706, -16.1890])\n",
      "Epoch: 1621,Loss: 3.036689\n",
      "\tgrad: tensor([-0.0335,  0.1895])\n",
      "\tparams: tensor([  5.1710, -16.1909])\n",
      "Epoch: 1622,Loss: 3.036319\n",
      "\tgrad: tensor([-0.0334,  0.1892])\n",
      "\tparams: tensor([  5.1713, -16.1928])\n",
      "Epoch: 1623,Loss: 3.035949\n",
      "\tgrad: tensor([-0.0334,  0.1889])\n",
      "\tparams: tensor([  5.1716, -16.1947])\n",
      "Epoch: 1624,Loss: 3.035583\n",
      "\tgrad: tensor([-0.0333,  0.1886])\n",
      "\tparams: tensor([  5.1720, -16.1966])\n",
      "Epoch: 1625,Loss: 3.035216\n",
      "\tgrad: tensor([-0.0333,  0.1883])\n",
      "\tparams: tensor([  5.1723, -16.1985])\n",
      "Epoch: 1626,Loss: 3.034849\n",
      "\tgrad: tensor([-0.0332,  0.1879])\n",
      "\tparams: tensor([  5.1726, -16.2003])\n",
      "Epoch: 1627,Loss: 3.034485\n",
      "\tgrad: tensor([-0.0331,  0.1876])\n",
      "\tparams: tensor([  5.1729, -16.2022])\n",
      "Epoch: 1628,Loss: 3.034123\n",
      "\tgrad: tensor([-0.0331,  0.1873])\n",
      "\tparams: tensor([  5.1733, -16.2041])\n",
      "Epoch: 1629,Loss: 3.033762\n",
      "\tgrad: tensor([-0.0330,  0.1870])\n",
      "\tparams: tensor([  5.1736, -16.2060])\n",
      "Epoch: 1630,Loss: 3.033402\n",
      "\tgrad: tensor([-0.0330,  0.1867])\n",
      "\tparams: tensor([  5.1739, -16.2078])\n",
      "Epoch: 1631,Loss: 3.033041\n",
      "\tgrad: tensor([-0.0329,  0.1863])\n",
      "\tparams: tensor([  5.1743, -16.2097])\n",
      "Epoch: 1632,Loss: 3.032685\n",
      "\tgrad: tensor([-0.0329,  0.1860])\n",
      "\tparams: tensor([  5.1746, -16.2116])\n",
      "Epoch: 1633,Loss: 3.032329\n",
      "\tgrad: tensor([-0.0328,  0.1857])\n",
      "\tparams: tensor([  5.1749, -16.2134])\n",
      "Epoch: 1634,Loss: 3.031973\n",
      "\tgrad: tensor([-0.0327,  0.1854])\n",
      "\tparams: tensor([  5.1753, -16.2153])\n",
      "Epoch: 1635,Loss: 3.031619\n",
      "\tgrad: tensor([-0.0327,  0.1851])\n",
      "\tparams: tensor([  5.1756, -16.2171])\n",
      "Epoch: 1636,Loss: 3.031265\n",
      "\tgrad: tensor([-0.0326,  0.1848])\n",
      "\tparams: tensor([  5.1759, -16.2190])\n",
      "Epoch: 1637,Loss: 3.030913\n",
      "\tgrad: tensor([-0.0326,  0.1845])\n",
      "\tparams: tensor([  5.1762, -16.2208])\n",
      "Epoch: 1638,Loss: 3.030564\n",
      "\tgrad: tensor([-0.0325,  0.1841])\n",
      "\tparams: tensor([  5.1766, -16.2226])\n",
      "Epoch: 1639,Loss: 3.030215\n",
      "\tgrad: tensor([-0.0325,  0.1838])\n",
      "\tparams: tensor([  5.1769, -16.2245])\n",
      "Epoch: 1640,Loss: 3.029867\n",
      "\tgrad: tensor([-0.0324,  0.1835])\n",
      "\tparams: tensor([  5.1772, -16.2263])\n",
      "Epoch: 1641,Loss: 3.029518\n",
      "\tgrad: tensor([-0.0324,  0.1832])\n",
      "\tparams: tensor([  5.1775, -16.2282])\n",
      "Epoch: 1642,Loss: 3.029173\n",
      "\tgrad: tensor([-0.0323,  0.1829])\n",
      "\tparams: tensor([  5.1779, -16.2300])\n",
      "Epoch: 1643,Loss: 3.028828\n",
      "\tgrad: tensor([-0.0323,  0.1826])\n",
      "\tparams: tensor([  5.1782, -16.2318])\n",
      "Epoch: 1644,Loss: 3.028486\n",
      "\tgrad: tensor([-0.0322,  0.1823])\n",
      "\tparams: tensor([  5.1785, -16.2336])\n",
      "Epoch: 1645,Loss: 3.028142\n",
      "\tgrad: tensor([-0.0321,  0.1820])\n",
      "\tparams: tensor([  5.1788, -16.2355])\n",
      "Epoch: 1646,Loss: 3.027802\n",
      "\tgrad: tensor([-0.0321,  0.1817])\n",
      "\tparams: tensor([  5.1791, -16.2373])\n",
      "Epoch: 1647,Loss: 3.027463\n",
      "\tgrad: tensor([-0.0320,  0.1813])\n",
      "\tparams: tensor([  5.1795, -16.2391])\n",
      "Epoch: 1648,Loss: 3.027122\n",
      "\tgrad: tensor([-0.0320,  0.1810])\n",
      "\tparams: tensor([  5.1798, -16.2409])\n",
      "Epoch: 1649,Loss: 3.026784\n",
      "\tgrad: tensor([-0.0319,  0.1807])\n",
      "\tparams: tensor([  5.1801, -16.2427])\n",
      "Epoch: 1650,Loss: 3.026447\n",
      "\tgrad: tensor([-0.0319,  0.1804])\n",
      "\tparams: tensor([  5.1804, -16.2445])\n",
      "Epoch: 1651,Loss: 3.026111\n",
      "\tgrad: tensor([-0.0318,  0.1801])\n",
      "\tparams: tensor([  5.1807, -16.2463])\n",
      "Epoch: 1652,Loss: 3.025780\n",
      "\tgrad: tensor([-0.0318,  0.1798])\n",
      "\tparams: tensor([  5.1811, -16.2481])\n",
      "Epoch: 1653,Loss: 3.025447\n",
      "\tgrad: tensor([-0.0317,  0.1795])\n",
      "\tparams: tensor([  5.1814, -16.2499])\n",
      "Epoch: 1654,Loss: 3.025114\n",
      "\tgrad: tensor([-0.0317,  0.1792])\n",
      "\tparams: tensor([  5.1817, -16.2517])\n",
      "Epoch: 1655,Loss: 3.024782\n",
      "\tgrad: tensor([-0.0316,  0.1789])\n",
      "\tparams: tensor([  5.1820, -16.2535])\n",
      "Epoch: 1656,Loss: 3.024452\n",
      "\tgrad: tensor([-0.0316,  0.1786])\n",
      "\tparams: tensor([  5.1823, -16.2553])\n",
      "Epoch: 1657,Loss: 3.024125\n",
      "\tgrad: tensor([-0.0315,  0.1783])\n",
      "\tparams: tensor([  5.1826, -16.2570])\n",
      "Epoch: 1658,Loss: 3.023796\n",
      "\tgrad: tensor([-0.0315,  0.1780])\n",
      "\tparams: tensor([  5.1829, -16.2588])\n",
      "Epoch: 1659,Loss: 3.023471\n",
      "\tgrad: tensor([-0.0314,  0.1777])\n",
      "\tparams: tensor([  5.1833, -16.2606])\n",
      "Epoch: 1660,Loss: 3.023145\n",
      "\tgrad: tensor([-0.0313,  0.1774])\n",
      "\tparams: tensor([  5.1836, -16.2624])\n",
      "Epoch: 1661,Loss: 3.022820\n",
      "\tgrad: tensor([-0.0313,  0.1771])\n",
      "\tparams: tensor([  5.1839, -16.2641])\n",
      "Epoch: 1662,Loss: 3.022498\n",
      "\tgrad: tensor([-0.0312,  0.1768])\n",
      "\tparams: tensor([  5.1842, -16.2659])\n",
      "Epoch: 1663,Loss: 3.022177\n",
      "\tgrad: tensor([-0.0312,  0.1765])\n",
      "\tparams: tensor([  5.1845, -16.2677])\n",
      "Epoch: 1664,Loss: 3.021855\n",
      "\tgrad: tensor([-0.0311,  0.1762])\n",
      "\tparams: tensor([  5.1848, -16.2694])\n",
      "Epoch: 1665,Loss: 3.021534\n",
      "\tgrad: tensor([-0.0311,  0.1759])\n",
      "\tparams: tensor([  5.1851, -16.2712])\n",
      "Epoch: 1666,Loss: 3.021217\n",
      "\tgrad: tensor([-0.0310,  0.1756])\n",
      "\tparams: tensor([  5.1854, -16.2730])\n",
      "Epoch: 1667,Loss: 3.020898\n",
      "\tgrad: tensor([-0.0310,  0.1753])\n",
      "\tparams: tensor([  5.1858, -16.2747])\n",
      "Epoch: 1668,Loss: 3.020582\n",
      "\tgrad: tensor([-0.0309,  0.1750])\n",
      "\tparams: tensor([  5.1861, -16.2765])\n",
      "Epoch: 1669,Loss: 3.020265\n",
      "\tgrad: tensor([-0.0309,  0.1747])\n",
      "\tparams: tensor([  5.1864, -16.2782])\n",
      "Epoch: 1670,Loss: 3.019952\n",
      "\tgrad: tensor([-0.0308,  0.1744])\n",
      "\tparams: tensor([  5.1867, -16.2800])\n",
      "Epoch: 1671,Loss: 3.019639\n",
      "\tgrad: tensor([-0.0308,  0.1741])\n",
      "\tparams: tensor([  5.1870, -16.2817])\n",
      "Epoch: 1672,Loss: 3.019325\n",
      "\tgrad: tensor([-0.0307,  0.1738])\n",
      "\tparams: tensor([  5.1873, -16.2834])\n",
      "Epoch: 1673,Loss: 3.019016\n",
      "\tgrad: tensor([-0.0307,  0.1735])\n",
      "\tparams: tensor([  5.1876, -16.2852])\n",
      "Epoch: 1674,Loss: 3.018706\n",
      "\tgrad: tensor([-0.0306,  0.1732])\n",
      "\tparams: tensor([  5.1879, -16.2869])\n",
      "Epoch: 1675,Loss: 3.018395\n",
      "\tgrad: tensor([-0.0305,  0.1729])\n",
      "\tparams: tensor([  5.1882, -16.2886])\n",
      "Epoch: 1676,Loss: 3.018089\n",
      "\tgrad: tensor([-0.0305,  0.1726])\n",
      "\tparams: tensor([  5.1885, -16.2904])\n",
      "Epoch: 1677,Loss: 3.017780\n",
      "\tgrad: tensor([-0.0304,  0.1723])\n",
      "\tparams: tensor([  5.1888, -16.2921])\n",
      "Epoch: 1678,Loss: 3.017475\n",
      "\tgrad: tensor([-0.0304,  0.1720])\n",
      "\tparams: tensor([  5.1891, -16.2938])\n",
      "Epoch: 1679,Loss: 3.017170\n",
      "\tgrad: tensor([-0.0303,  0.1717])\n",
      "\tparams: tensor([  5.1894, -16.2955])\n",
      "Epoch: 1680,Loss: 3.016867\n",
      "\tgrad: tensor([-0.0303,  0.1715])\n",
      "\tparams: tensor([  5.1897, -16.2972])\n",
      "Epoch: 1681,Loss: 3.016564\n",
      "\tgrad: tensor([-0.0302,  0.1712])\n",
      "\tparams: tensor([  5.1900, -16.2989])\n",
      "Epoch: 1682,Loss: 3.016262\n",
      "\tgrad: tensor([-0.0302,  0.1709])\n",
      "\tparams: tensor([  5.1903, -16.3006])\n",
      "Epoch: 1683,Loss: 3.015959\n",
      "\tgrad: tensor([-0.0301,  0.1706])\n",
      "\tparams: tensor([  5.1906, -16.3024])\n",
      "Epoch: 1684,Loss: 3.015662\n",
      "\tgrad: tensor([-0.0301,  0.1703])\n",
      "\tparams: tensor([  5.1909, -16.3041])\n",
      "Epoch: 1685,Loss: 3.015361\n",
      "\tgrad: tensor([-0.0300,  0.1700])\n",
      "\tparams: tensor([  5.1912, -16.3058])\n",
      "Epoch: 1686,Loss: 3.015064\n",
      "\tgrad: tensor([-0.0300,  0.1697])\n",
      "\tparams: tensor([  5.1915, -16.3075])\n",
      "Epoch: 1687,Loss: 3.014768\n",
      "\tgrad: tensor([-0.0299,  0.1694])\n",
      "\tparams: tensor([  5.1918, -16.3091])\n",
      "Epoch: 1688,Loss: 3.014472\n",
      "\tgrad: tensor([-0.0299,  0.1691])\n",
      "\tparams: tensor([  5.1921, -16.3108])\n",
      "Epoch: 1689,Loss: 3.014179\n",
      "\tgrad: tensor([-0.0298,  0.1688])\n",
      "\tparams: tensor([  5.1924, -16.3125])\n",
      "Epoch: 1690,Loss: 3.013884\n",
      "\tgrad: tensor([-0.0298,  0.1686])\n",
      "\tparams: tensor([  5.1927, -16.3142])\n",
      "Epoch: 1691,Loss: 3.013591\n",
      "\tgrad: tensor([-0.0297,  0.1683])\n",
      "\tparams: tensor([  5.1930, -16.3159])\n",
      "Epoch: 1692,Loss: 3.013299\n",
      "\tgrad: tensor([-0.0297,  0.1680])\n",
      "\tparams: tensor([  5.1933, -16.3176])\n",
      "Epoch: 1693,Loss: 3.013008\n",
      "\tgrad: tensor([-0.0296,  0.1677])\n",
      "\tparams: tensor([  5.1936, -16.3193])\n",
      "Epoch: 1694,Loss: 3.012719\n",
      "\tgrad: tensor([-0.0296,  0.1674])\n",
      "\tparams: tensor([  5.1939, -16.3209])\n",
      "Epoch: 1695,Loss: 3.012431\n",
      "\tgrad: tensor([-0.0295,  0.1671])\n",
      "\tparams: tensor([  5.1942, -16.3226])\n",
      "Epoch: 1696,Loss: 3.012141\n",
      "\tgrad: tensor([-0.0295,  0.1668])\n",
      "\tparams: tensor([  5.1945, -16.3243])\n",
      "Epoch: 1697,Loss: 3.011855\n",
      "\tgrad: tensor([-0.0294,  0.1666])\n",
      "\tparams: tensor([  5.1948, -16.3259])\n",
      "Epoch: 1698,Loss: 3.011570\n",
      "\tgrad: tensor([-0.0294,  0.1663])\n",
      "\tparams: tensor([  5.1951, -16.3276])\n",
      "Epoch: 1699,Loss: 3.011284\n",
      "\tgrad: tensor([-0.0293,  0.1660])\n",
      "\tparams: tensor([  5.1954, -16.3293])\n",
      "Epoch: 1700,Loss: 3.011001\n",
      "\tgrad: tensor([-0.0293,  0.1657])\n",
      "\tparams: tensor([  5.1957, -16.3309])\n",
      "Epoch: 1701,Loss: 3.010718\n",
      "\tgrad: tensor([-0.0292,  0.1654])\n",
      "\tparams: tensor([  5.1960, -16.3326])\n",
      "Epoch: 1702,Loss: 3.010436\n",
      "\tgrad: tensor([-0.0292,  0.1652])\n",
      "\tparams: tensor([  5.1963, -16.3342])\n",
      "Epoch: 1703,Loss: 3.010156\n",
      "\tgrad: tensor([-0.0291,  0.1649])\n",
      "\tparams: tensor([  5.1966, -16.3359])\n",
      "Epoch: 1704,Loss: 3.009876\n",
      "\tgrad: tensor([-0.0291,  0.1646])\n",
      "\tparams: tensor([  5.1968, -16.3375])\n",
      "Epoch: 1705,Loss: 3.009595\n",
      "\tgrad: tensor([-0.0290,  0.1643])\n",
      "\tparams: tensor([  5.1971, -16.3392])\n",
      "Epoch: 1706,Loss: 3.009319\n",
      "\tgrad: tensor([-0.0290,  0.1640])\n",
      "\tparams: tensor([  5.1974, -16.3408])\n",
      "Epoch: 1707,Loss: 3.009040\n",
      "\tgrad: tensor([-0.0289,  0.1638])\n",
      "\tparams: tensor([  5.1977, -16.3424])\n",
      "Epoch: 1708,Loss: 3.008763\n",
      "\tgrad: tensor([-0.0289,  0.1635])\n",
      "\tparams: tensor([  5.1980, -16.3441])\n",
      "Epoch: 1709,Loss: 3.008487\n",
      "\tgrad: tensor([-0.0288,  0.1632])\n",
      "\tparams: tensor([  5.1983, -16.3457])\n",
      "Epoch: 1710,Loss: 3.008215\n",
      "\tgrad: tensor([-0.0288,  0.1629])\n",
      "\tparams: tensor([  5.1986, -16.3473])\n",
      "Epoch: 1711,Loss: 3.007941\n",
      "\tgrad: tensor([-0.0287,  0.1626])\n",
      "\tparams: tensor([  5.1989, -16.3490])\n",
      "Epoch: 1712,Loss: 3.007668\n",
      "\tgrad: tensor([-0.0287,  0.1624])\n",
      "\tparams: tensor([  5.1992, -16.3506])\n",
      "Epoch: 1713,Loss: 3.007397\n",
      "\tgrad: tensor([-0.0286,  0.1621])\n",
      "\tparams: tensor([  5.1994, -16.3522])\n",
      "Epoch: 1714,Loss: 3.007126\n",
      "\tgrad: tensor([-0.0286,  0.1618])\n",
      "\tparams: tensor([  5.1997, -16.3538])\n",
      "Epoch: 1715,Loss: 3.006857\n",
      "\tgrad: tensor([-0.0285,  0.1615])\n",
      "\tparams: tensor([  5.2000, -16.3554])\n",
      "Epoch: 1716,Loss: 3.006586\n",
      "\tgrad: tensor([-0.0285,  0.1613])\n",
      "\tparams: tensor([  5.2003, -16.3570])\n",
      "Epoch: 1717,Loss: 3.006318\n",
      "\tgrad: tensor([-0.0284,  0.1610])\n",
      "\tparams: tensor([  5.2006, -16.3587])\n",
      "Epoch: 1718,Loss: 3.006052\n",
      "\tgrad: tensor([-0.0284,  0.1607])\n",
      "\tparams: tensor([  5.2009, -16.3603])\n",
      "Epoch: 1719,Loss: 3.005785\n",
      "\tgrad: tensor([-0.0284,  0.1604])\n",
      "\tparams: tensor([  5.2012, -16.3619])\n",
      "Epoch: 1720,Loss: 3.005521\n",
      "\tgrad: tensor([-0.0283,  0.1602])\n",
      "\tparams: tensor([  5.2014, -16.3635])\n",
      "Epoch: 1721,Loss: 3.005256\n",
      "\tgrad: tensor([-0.0283,  0.1599])\n",
      "\tparams: tensor([  5.2017, -16.3651])\n",
      "Epoch: 1722,Loss: 3.004993\n",
      "\tgrad: tensor([-0.0282,  0.1596])\n",
      "\tparams: tensor([  5.2020, -16.3667])\n",
      "Epoch: 1723,Loss: 3.004729\n",
      "\tgrad: tensor([-0.0281,  0.1594])\n",
      "\tparams: tensor([  5.2023, -16.3683])\n",
      "Epoch: 1724,Loss: 3.004467\n",
      "\tgrad: tensor([-0.0281,  0.1591])\n",
      "\tparams: tensor([  5.2026, -16.3699])\n",
      "Epoch: 1725,Loss: 3.004207\n",
      "\tgrad: tensor([-0.0280,  0.1588])\n",
      "\tparams: tensor([  5.2028, -16.3714])\n",
      "Epoch: 1726,Loss: 3.003947\n",
      "\tgrad: tensor([-0.0280,  0.1586])\n",
      "\tparams: tensor([  5.2031, -16.3730])\n",
      "Epoch: 1727,Loss: 3.003690\n",
      "\tgrad: tensor([-0.0280,  0.1583])\n",
      "\tparams: tensor([  5.2034, -16.3746])\n",
      "Epoch: 1728,Loss: 3.003431\n",
      "\tgrad: tensor([-0.0279,  0.1580])\n",
      "\tparams: tensor([  5.2037, -16.3762])\n",
      "Epoch: 1729,Loss: 3.003174\n",
      "\tgrad: tensor([-0.0279,  0.1577])\n",
      "\tparams: tensor([  5.2040, -16.3778])\n",
      "Epoch: 1730,Loss: 3.002918\n",
      "\tgrad: tensor([-0.0278,  0.1575])\n",
      "\tparams: tensor([  5.2042, -16.3793])\n",
      "Epoch: 1731,Loss: 3.002661\n",
      "\tgrad: tensor([-0.0278,  0.1572])\n",
      "\tparams: tensor([  5.2045, -16.3809])\n",
      "Epoch: 1732,Loss: 3.002406\n",
      "\tgrad: tensor([-0.0277,  0.1569])\n",
      "\tparams: tensor([  5.2048, -16.3825])\n",
      "Epoch: 1733,Loss: 3.002152\n",
      "\tgrad: tensor([-0.0277,  0.1567])\n",
      "\tparams: tensor([  5.2051, -16.3840])\n",
      "Epoch: 1734,Loss: 3.001901\n",
      "\tgrad: tensor([-0.0276,  0.1564])\n",
      "\tparams: tensor([  5.2053, -16.3856])\n",
      "Epoch: 1735,Loss: 3.001649\n",
      "\tgrad: tensor([-0.0276,  0.1561])\n",
      "\tparams: tensor([  5.2056, -16.3872])\n",
      "Epoch: 1736,Loss: 3.001395\n",
      "\tgrad: tensor([-0.0275,  0.1559])\n",
      "\tparams: tensor([  5.2059, -16.3887])\n",
      "Epoch: 1737,Loss: 3.001145\n",
      "\tgrad: tensor([-0.0275,  0.1556])\n",
      "\tparams: tensor([  5.2062, -16.3903])\n",
      "Epoch: 1738,Loss: 3.000898\n",
      "\tgrad: tensor([-0.0274,  0.1553])\n",
      "\tparams: tensor([  5.2064, -16.3918])\n",
      "Epoch: 1739,Loss: 3.000648\n",
      "\tgrad: tensor([-0.0274,  0.1551])\n",
      "\tparams: tensor([  5.2067, -16.3934])\n",
      "Epoch: 1740,Loss: 3.000400\n",
      "\tgrad: tensor([-0.0273,  0.1548])\n",
      "\tparams: tensor([  5.2070, -16.3949])\n",
      "Epoch: 1741,Loss: 3.000154\n",
      "\tgrad: tensor([-0.0273,  0.1546])\n",
      "\tparams: tensor([  5.2073, -16.3965])\n",
      "Epoch: 1742,Loss: 2.999907\n",
      "\tgrad: tensor([-0.0273,  0.1543])\n",
      "\tparams: tensor([  5.2075, -16.3980])\n",
      "Epoch: 1743,Loss: 2.999662\n",
      "\tgrad: tensor([-0.0272,  0.1540])\n",
      "\tparams: tensor([  5.2078, -16.3996])\n",
      "Epoch: 1744,Loss: 2.999417\n",
      "\tgrad: tensor([-0.0272,  0.1538])\n",
      "\tparams: tensor([  5.2081, -16.4011])\n",
      "Epoch: 1745,Loss: 2.999174\n",
      "\tgrad: tensor([-0.0271,  0.1535])\n",
      "\tparams: tensor([  5.2084, -16.4026])\n",
      "Epoch: 1746,Loss: 2.998930\n",
      "\tgrad: tensor([-0.0271,  0.1533])\n",
      "\tparams: tensor([  5.2086, -16.4042])\n",
      "Epoch: 1747,Loss: 2.998688\n",
      "\tgrad: tensor([-0.0270,  0.1530])\n",
      "\tparams: tensor([  5.2089, -16.4057])\n",
      "Epoch: 1748,Loss: 2.998448\n",
      "\tgrad: tensor([-0.0270,  0.1527])\n",
      "\tparams: tensor([  5.2092, -16.4072])\n",
      "Epoch: 1749,Loss: 2.998208\n",
      "\tgrad: tensor([-0.0269,  0.1525])\n",
      "\tparams: tensor([  5.2094, -16.4088])\n",
      "Epoch: 1750,Loss: 2.997968\n",
      "\tgrad: tensor([-0.0269,  0.1522])\n",
      "\tparams: tensor([  5.2097, -16.4103])\n",
      "Epoch: 1751,Loss: 2.997730\n",
      "\tgrad: tensor([-0.0268,  0.1520])\n",
      "\tparams: tensor([  5.2100, -16.4118])\n",
      "Epoch: 1752,Loss: 2.997490\n",
      "\tgrad: tensor([-0.0268,  0.1517])\n",
      "\tparams: tensor([  5.2102, -16.4133])\n",
      "Epoch: 1753,Loss: 2.997254\n",
      "\tgrad: tensor([-0.0267,  0.1514])\n",
      "\tparams: tensor([  5.2105, -16.4148])\n",
      "Epoch: 1754,Loss: 2.997018\n",
      "\tgrad: tensor([-0.0267,  0.1512])\n",
      "\tparams: tensor([  5.2108, -16.4163])\n",
      "Epoch: 1755,Loss: 2.996782\n",
      "\tgrad: tensor([-0.0266,  0.1509])\n",
      "\tparams: tensor([  5.2110, -16.4179])\n",
      "Epoch: 1756,Loss: 2.996548\n",
      "\tgrad: tensor([-0.0266,  0.1507])\n",
      "\tparams: tensor([  5.2113, -16.4194])\n",
      "Epoch: 1757,Loss: 2.996313\n",
      "\tgrad: tensor([-0.0266,  0.1504])\n",
      "\tparams: tensor([  5.2116, -16.4209])\n",
      "Epoch: 1758,Loss: 2.996081\n",
      "\tgrad: tensor([-0.0265,  0.1502])\n",
      "\tparams: tensor([  5.2118, -16.4224])\n",
      "Epoch: 1759,Loss: 2.995847\n",
      "\tgrad: tensor([-0.0265,  0.1499])\n",
      "\tparams: tensor([  5.2121, -16.4239])\n",
      "Epoch: 1760,Loss: 2.995615\n",
      "\tgrad: tensor([-0.0264,  0.1496])\n",
      "\tparams: tensor([  5.2124, -16.4254])\n",
      "Epoch: 1761,Loss: 2.995387\n",
      "\tgrad: tensor([-0.0264,  0.1494])\n",
      "\tparams: tensor([  5.2126, -16.4269])\n",
      "Epoch: 1762,Loss: 2.995156\n",
      "\tgrad: tensor([-0.0263,  0.1491])\n",
      "\tparams: tensor([  5.2129, -16.4283])\n",
      "Epoch: 1763,Loss: 2.994928\n",
      "\tgrad: tensor([-0.0263,  0.1489])\n",
      "\tparams: tensor([  5.2132, -16.4298])\n",
      "Epoch: 1764,Loss: 2.994699\n",
      "\tgrad: tensor([-0.0263,  0.1486])\n",
      "\tparams: tensor([  5.2134, -16.4313])\n",
      "Epoch: 1765,Loss: 2.994471\n",
      "\tgrad: tensor([-0.0262,  0.1484])\n",
      "\tparams: tensor([  5.2137, -16.4328])\n",
      "Epoch: 1766,Loss: 2.994245\n",
      "\tgrad: tensor([-0.0262,  0.1481])\n",
      "\tparams: tensor([  5.2139, -16.4343])\n",
      "Epoch: 1767,Loss: 2.994019\n",
      "\tgrad: tensor([-0.0261,  0.1479])\n",
      "\tparams: tensor([  5.2142, -16.4358])\n",
      "Epoch: 1768,Loss: 2.993794\n",
      "\tgrad: tensor([-0.0261,  0.1476])\n",
      "\tparams: tensor([  5.2145, -16.4372])\n",
      "Epoch: 1769,Loss: 2.993569\n",
      "\tgrad: tensor([-0.0260,  0.1474])\n",
      "\tparams: tensor([  5.2147, -16.4387])\n",
      "Epoch: 1770,Loss: 2.993344\n",
      "\tgrad: tensor([-0.0260,  0.1471])\n",
      "\tparams: tensor([  5.2150, -16.4402])\n",
      "Epoch: 1771,Loss: 2.993121\n",
      "\tgrad: tensor([-0.0260,  0.1469])\n",
      "\tparams: tensor([  5.2152, -16.4417])\n",
      "Epoch: 1772,Loss: 2.992900\n",
      "\tgrad: tensor([-0.0259,  0.1466])\n",
      "\tparams: tensor([  5.2155, -16.4431])\n",
      "Epoch: 1773,Loss: 2.992678\n",
      "\tgrad: tensor([-0.0259,  0.1464])\n",
      "\tparams: tensor([  5.2158, -16.4446])\n",
      "Epoch: 1774,Loss: 2.992457\n",
      "\tgrad: tensor([-0.0258,  0.1461])\n",
      "\tparams: tensor([  5.2160, -16.4460])\n",
      "Epoch: 1775,Loss: 2.992237\n",
      "\tgrad: tensor([-0.0258,  0.1459])\n",
      "\tparams: tensor([  5.2163, -16.4475])\n",
      "Epoch: 1776,Loss: 2.992017\n",
      "\tgrad: tensor([-0.0257,  0.1456])\n",
      "\tparams: tensor([  5.2165, -16.4490])\n",
      "Epoch: 1777,Loss: 2.991798\n",
      "\tgrad: tensor([-0.0257,  0.1454])\n",
      "\tparams: tensor([  5.2168, -16.4504])\n",
      "Epoch: 1778,Loss: 2.991582\n",
      "\tgrad: tensor([-0.0256,  0.1451])\n",
      "\tparams: tensor([  5.2170, -16.4519])\n",
      "Epoch: 1779,Loss: 2.991366\n",
      "\tgrad: tensor([-0.0256,  0.1449])\n",
      "\tparams: tensor([  5.2173, -16.4533])\n",
      "Epoch: 1780,Loss: 2.991146\n",
      "\tgrad: tensor([-0.0256,  0.1446])\n",
      "\tparams: tensor([  5.2176, -16.4548])\n",
      "Epoch: 1781,Loss: 2.990932\n",
      "\tgrad: tensor([-0.0255,  0.1444])\n",
      "\tparams: tensor([  5.2178, -16.4562])\n",
      "Epoch: 1782,Loss: 2.990719\n",
      "\tgrad: tensor([-0.0255,  0.1442])\n",
      "\tparams: tensor([  5.2181, -16.4576])\n",
      "Epoch: 1783,Loss: 2.990503\n",
      "\tgrad: tensor([-0.0254,  0.1439])\n",
      "\tparams: tensor([  5.2183, -16.4591])\n",
      "Epoch: 1784,Loss: 2.990288\n",
      "\tgrad: tensor([-0.0254,  0.1437])\n",
      "\tparams: tensor([  5.2186, -16.4605])\n",
      "Epoch: 1785,Loss: 2.990078\n",
      "\tgrad: tensor([-0.0253,  0.1434])\n",
      "\tparams: tensor([  5.2188, -16.4620])\n",
      "Epoch: 1786,Loss: 2.989866\n",
      "\tgrad: tensor([-0.0253,  0.1432])\n",
      "\tparams: tensor([  5.2191, -16.4634])\n",
      "Epoch: 1787,Loss: 2.989655\n",
      "\tgrad: tensor([-0.0252,  0.1429])\n",
      "\tparams: tensor([  5.2193, -16.4648])\n",
      "Epoch: 1788,Loss: 2.989443\n",
      "\tgrad: tensor([-0.0252,  0.1427])\n",
      "\tparams: tensor([  5.2196, -16.4662])\n",
      "Epoch: 1789,Loss: 2.989233\n",
      "\tgrad: tensor([-0.0252,  0.1424])\n",
      "\tparams: tensor([  5.2198, -16.4677])\n",
      "Epoch: 1790,Loss: 2.989025\n",
      "\tgrad: tensor([-0.0251,  0.1422])\n",
      "\tparams: tensor([  5.2201, -16.4691])\n",
      "Epoch: 1791,Loss: 2.988817\n",
      "\tgrad: tensor([-0.0251,  0.1420])\n",
      "\tparams: tensor([  5.2203, -16.4705])\n",
      "Epoch: 1792,Loss: 2.988609\n",
      "\tgrad: tensor([-0.0250,  0.1417])\n",
      "\tparams: tensor([  5.2206, -16.4719])\n",
      "Epoch: 1793,Loss: 2.988401\n",
      "\tgrad: tensor([-0.0250,  0.1415])\n",
      "\tparams: tensor([  5.2208, -16.4733])\n",
      "Epoch: 1794,Loss: 2.988195\n",
      "\tgrad: tensor([-0.0249,  0.1412])\n",
      "\tparams: tensor([  5.2211, -16.4748])\n",
      "Epoch: 1795,Loss: 2.987989\n",
      "\tgrad: tensor([-0.0249,  0.1410])\n",
      "\tparams: tensor([  5.2213, -16.4762])\n",
      "Epoch: 1796,Loss: 2.987785\n",
      "\tgrad: tensor([-0.0249,  0.1408])\n",
      "\tparams: tensor([  5.2216, -16.4776])\n",
      "Epoch: 1797,Loss: 2.987582\n",
      "\tgrad: tensor([-0.0248,  0.1405])\n",
      "\tparams: tensor([  5.2218, -16.4790])\n",
      "Epoch: 1798,Loss: 2.987377\n",
      "\tgrad: tensor([-0.0248,  0.1403])\n",
      "\tparams: tensor([  5.2221, -16.4804])\n",
      "Epoch: 1799,Loss: 2.987174\n",
      "\tgrad: tensor([-0.0247,  0.1400])\n",
      "\tparams: tensor([  5.2223, -16.4818])\n",
      "Epoch: 1800,Loss: 2.986974\n",
      "\tgrad: tensor([-0.0247,  0.1398])\n",
      "\tparams: tensor([  5.2226, -16.4832])\n",
      "Epoch: 1801,Loss: 2.986771\n",
      "\tgrad: tensor([-0.0246,  0.1396])\n",
      "\tparams: tensor([  5.2228, -16.4846])\n",
      "Epoch: 1802,Loss: 2.986570\n",
      "\tgrad: tensor([-0.0246,  0.1393])\n",
      "\tparams: tensor([  5.2231, -16.4860])\n",
      "Epoch: 1803,Loss: 2.986371\n",
      "\tgrad: tensor([-0.0246,  0.1391])\n",
      "\tparams: tensor([  5.2233, -16.4874])\n",
      "Epoch: 1804,Loss: 2.986171\n",
      "\tgrad: tensor([-0.0245,  0.1389])\n",
      "\tparams: tensor([  5.2236, -16.4888])\n",
      "Epoch: 1805,Loss: 2.985972\n",
      "\tgrad: tensor([-0.0245,  0.1386])\n",
      "\tparams: tensor([  5.2238, -16.4901])\n",
      "Epoch: 1806,Loss: 2.985774\n",
      "\tgrad: tensor([-0.0245,  0.1384])\n",
      "\tparams: tensor([  5.2241, -16.4915])\n",
      "Epoch: 1807,Loss: 2.985578\n",
      "\tgrad: tensor([-0.0244,  0.1382])\n",
      "\tparams: tensor([  5.2243, -16.4929])\n",
      "Epoch: 1808,Loss: 2.985381\n",
      "\tgrad: tensor([-0.0244,  0.1379])\n",
      "\tparams: tensor([  5.2245, -16.4943])\n",
      "Epoch: 1809,Loss: 2.985184\n",
      "\tgrad: tensor([-0.0243,  0.1377])\n",
      "\tparams: tensor([  5.2248, -16.4957])\n",
      "Epoch: 1810,Loss: 2.984989\n",
      "\tgrad: tensor([-0.0243,  0.1374])\n",
      "\tparams: tensor([  5.2250, -16.4970])\n",
      "Epoch: 1811,Loss: 2.984793\n",
      "\tgrad: tensor([-0.0243,  0.1372])\n",
      "\tparams: tensor([  5.2253, -16.4984])\n",
      "Epoch: 1812,Loss: 2.984601\n",
      "\tgrad: tensor([-0.0242,  0.1370])\n",
      "\tparams: tensor([  5.2255, -16.4998])\n",
      "Epoch: 1813,Loss: 2.984407\n",
      "\tgrad: tensor([-0.0242,  0.1368])\n",
      "\tparams: tensor([  5.2258, -16.5011])\n",
      "Epoch: 1814,Loss: 2.984215\n",
      "\tgrad: tensor([-0.0241,  0.1365])\n",
      "\tparams: tensor([  5.2260, -16.5025])\n",
      "Epoch: 1815,Loss: 2.984022\n",
      "\tgrad: tensor([-0.0241,  0.1363])\n",
      "\tparams: tensor([  5.2262, -16.5039])\n",
      "Epoch: 1816,Loss: 2.983831\n",
      "\tgrad: tensor([-0.0240,  0.1361])\n",
      "\tparams: tensor([  5.2265, -16.5052])\n",
      "Epoch: 1817,Loss: 2.983639\n",
      "\tgrad: tensor([-0.0240,  0.1358])\n",
      "\tparams: tensor([  5.2267, -16.5066])\n",
      "Epoch: 1818,Loss: 2.983449\n",
      "\tgrad: tensor([-0.0239,  0.1356])\n",
      "\tparams: tensor([  5.2270, -16.5079])\n",
      "Epoch: 1819,Loss: 2.983259\n",
      "\tgrad: tensor([-0.0239,  0.1354])\n",
      "\tparams: tensor([  5.2272, -16.5093])\n",
      "Epoch: 1820,Loss: 2.983073\n",
      "\tgrad: tensor([-0.0239,  0.1351])\n",
      "\tparams: tensor([  5.2274, -16.5107])\n",
      "Epoch: 1821,Loss: 2.982884\n",
      "\tgrad: tensor([-0.0238,  0.1349])\n",
      "\tparams: tensor([  5.2277, -16.5120])\n",
      "Epoch: 1822,Loss: 2.982697\n",
      "\tgrad: tensor([-0.0238,  0.1347])\n",
      "\tparams: tensor([  5.2279, -16.5133])\n",
      "Epoch: 1823,Loss: 2.982510\n",
      "\tgrad: tensor([-0.0237,  0.1344])\n",
      "\tparams: tensor([  5.2281, -16.5147])\n",
      "Epoch: 1824,Loss: 2.982322\n",
      "\tgrad: tensor([-0.0237,  0.1342])\n",
      "\tparams: tensor([  5.2284, -16.5160])\n",
      "Epoch: 1825,Loss: 2.982137\n",
      "\tgrad: tensor([-0.0237,  0.1340])\n",
      "\tparams: tensor([  5.2286, -16.5174])\n",
      "Epoch: 1826,Loss: 2.981953\n",
      "\tgrad: tensor([-0.0236,  0.1338])\n",
      "\tparams: tensor([  5.2289, -16.5187])\n",
      "Epoch: 1827,Loss: 2.981769\n",
      "\tgrad: tensor([-0.0236,  0.1335])\n",
      "\tparams: tensor([  5.2291, -16.5200])\n",
      "Epoch: 1828,Loss: 2.981586\n",
      "\tgrad: tensor([-0.0236,  0.1333])\n",
      "\tparams: tensor([  5.2293, -16.5214])\n",
      "Epoch: 1829,Loss: 2.981402\n",
      "\tgrad: tensor([-0.0235,  0.1331])\n",
      "\tparams: tensor([  5.2296, -16.5227])\n",
      "Epoch: 1830,Loss: 2.981219\n",
      "\tgrad: tensor([-0.0235,  0.1329])\n",
      "\tparams: tensor([  5.2298, -16.5240])\n",
      "Epoch: 1831,Loss: 2.981037\n",
      "\tgrad: tensor([-0.0235,  0.1326])\n",
      "\tparams: tensor([  5.2300, -16.5254])\n",
      "Epoch: 1832,Loss: 2.980856\n",
      "\tgrad: tensor([-0.0234,  0.1324])\n",
      "\tparams: tensor([  5.2303, -16.5267])\n",
      "Epoch: 1833,Loss: 2.980675\n",
      "\tgrad: tensor([-0.0234,  0.1322])\n",
      "\tparams: tensor([  5.2305, -16.5280])\n",
      "Epoch: 1834,Loss: 2.980495\n",
      "\tgrad: tensor([-0.0233,  0.1320])\n",
      "\tparams: tensor([  5.2307, -16.5293])\n",
      "Epoch: 1835,Loss: 2.980315\n",
      "\tgrad: tensor([-0.0233,  0.1317])\n",
      "\tparams: tensor([  5.2310, -16.5306])\n",
      "Epoch: 1836,Loss: 2.980137\n",
      "\tgrad: tensor([-0.0232,  0.1315])\n",
      "\tparams: tensor([  5.2312, -16.5320])\n",
      "Epoch: 1837,Loss: 2.979958\n",
      "\tgrad: tensor([-0.0232,  0.1313])\n",
      "\tparams: tensor([  5.2314, -16.5333])\n",
      "Epoch: 1838,Loss: 2.979782\n",
      "\tgrad: tensor([-0.0232,  0.1311])\n",
      "\tparams: tensor([  5.2317, -16.5346])\n",
      "Epoch: 1839,Loss: 2.979604\n",
      "\tgrad: tensor([-0.0231,  0.1308])\n",
      "\tparams: tensor([  5.2319, -16.5359])\n",
      "Epoch: 1840,Loss: 2.979428\n",
      "\tgrad: tensor([-0.0231,  0.1306])\n",
      "\tparams: tensor([  5.2321, -16.5372])\n",
      "Epoch: 1841,Loss: 2.979253\n",
      "\tgrad: tensor([-0.0230,  0.1304])\n",
      "\tparams: tensor([  5.2324, -16.5385])\n",
      "Epoch: 1842,Loss: 2.979078\n",
      "\tgrad: tensor([-0.0230,  0.1302])\n",
      "\tparams: tensor([  5.2326, -16.5398])\n",
      "Epoch: 1843,Loss: 2.978902\n",
      "\tgrad: tensor([-0.0229,  0.1300])\n",
      "\tparams: tensor([  5.2328, -16.5411])\n",
      "Epoch: 1844,Loss: 2.978729\n",
      "\tgrad: tensor([-0.0229,  0.1297])\n",
      "\tparams: tensor([  5.2330, -16.5424])\n",
      "Epoch: 1845,Loss: 2.978556\n",
      "\tgrad: tensor([-0.0229,  0.1295])\n",
      "\tparams: tensor([  5.2333, -16.5437])\n",
      "Epoch: 1846,Loss: 2.978382\n",
      "\tgrad: tensor([-0.0228,  0.1293])\n",
      "\tparams: tensor([  5.2335, -16.5450])\n",
      "Epoch: 1847,Loss: 2.978211\n",
      "\tgrad: tensor([-0.0228,  0.1291])\n",
      "\tparams: tensor([  5.2337, -16.5463])\n",
      "Epoch: 1848,Loss: 2.978039\n",
      "\tgrad: tensor([-0.0228,  0.1288])\n",
      "\tparams: tensor([  5.2340, -16.5476])\n",
      "Epoch: 1849,Loss: 2.977867\n",
      "\tgrad: tensor([-0.0227,  0.1286])\n",
      "\tparams: tensor([  5.2342, -16.5489])\n",
      "Epoch: 1850,Loss: 2.977696\n",
      "\tgrad: tensor([-0.0227,  0.1284])\n",
      "\tparams: tensor([  5.2344, -16.5501])\n",
      "Epoch: 1851,Loss: 2.977527\n",
      "\tgrad: tensor([-0.0227,  0.1282])\n",
      "\tparams: tensor([  5.2346, -16.5514])\n",
      "Epoch: 1852,Loss: 2.977357\n",
      "\tgrad: tensor([-0.0226,  0.1280])\n",
      "\tparams: tensor([  5.2349, -16.5527])\n",
      "Epoch: 1853,Loss: 2.977188\n",
      "\tgrad: tensor([-0.0226,  0.1278])\n",
      "\tparams: tensor([  5.2351, -16.5540])\n",
      "Epoch: 1854,Loss: 2.977021\n",
      "\tgrad: tensor([-0.0225,  0.1275])\n",
      "\tparams: tensor([  5.2353, -16.5553])\n",
      "Epoch: 1855,Loss: 2.976853\n",
      "\tgrad: tensor([-0.0225,  0.1273])\n",
      "\tparams: tensor([  5.2355, -16.5565])\n",
      "Epoch: 1856,Loss: 2.976687\n",
      "\tgrad: tensor([-0.0225,  0.1271])\n",
      "\tparams: tensor([  5.2358, -16.5578])\n",
      "Epoch: 1857,Loss: 2.976520\n",
      "\tgrad: tensor([-0.0224,  0.1269])\n",
      "\tparams: tensor([  5.2360, -16.5591])\n",
      "Epoch: 1858,Loss: 2.976354\n",
      "\tgrad: tensor([-0.0224,  0.1267])\n",
      "\tparams: tensor([  5.2362, -16.5603])\n",
      "Epoch: 1859,Loss: 2.976189\n",
      "\tgrad: tensor([-0.0223,  0.1265])\n",
      "\tparams: tensor([  5.2364, -16.5616])\n",
      "Epoch: 1860,Loss: 2.976023\n",
      "\tgrad: tensor([-0.0223,  0.1263])\n",
      "\tparams: tensor([  5.2367, -16.5629])\n",
      "Epoch: 1861,Loss: 2.975860\n",
      "\tgrad: tensor([-0.0223,  0.1260])\n",
      "\tparams: tensor([  5.2369, -16.5641])\n",
      "Epoch: 1862,Loss: 2.975697\n",
      "\tgrad: tensor([-0.0222,  0.1258])\n",
      "\tparams: tensor([  5.2371, -16.5654])\n",
      "Epoch: 1863,Loss: 2.975533\n",
      "\tgrad: tensor([-0.0222,  0.1256])\n",
      "\tparams: tensor([  5.2373, -16.5666])\n",
      "Epoch: 1864,Loss: 2.975369\n",
      "\tgrad: tensor([-0.0222,  0.1254])\n",
      "\tparams: tensor([  5.2375, -16.5679])\n",
      "Epoch: 1865,Loss: 2.975208\n",
      "\tgrad: tensor([-0.0221,  0.1252])\n",
      "\tparams: tensor([  5.2378, -16.5691])\n",
      "Epoch: 1866,Loss: 2.975046\n",
      "\tgrad: tensor([-0.0221,  0.1250])\n",
      "\tparams: tensor([  5.2380, -16.5704])\n",
      "Epoch: 1867,Loss: 2.974886\n",
      "\tgrad: tensor([-0.0220,  0.1248])\n",
      "\tparams: tensor([  5.2382, -16.5716])\n",
      "Epoch: 1868,Loss: 2.974725\n",
      "\tgrad: tensor([-0.0220,  0.1245])\n",
      "\tparams: tensor([  5.2384, -16.5729])\n",
      "Epoch: 1869,Loss: 2.974565\n",
      "\tgrad: tensor([-0.0220,  0.1243])\n",
      "\tparams: tensor([  5.2386, -16.5741])\n",
      "Epoch: 1870,Loss: 2.974406\n",
      "\tgrad: tensor([-0.0219,  0.1241])\n",
      "\tparams: tensor([  5.2389, -16.5754])\n",
      "Epoch: 1871,Loss: 2.974248\n",
      "\tgrad: tensor([-0.0219,  0.1239])\n",
      "\tparams: tensor([  5.2391, -16.5766])\n",
      "Epoch: 1872,Loss: 2.974088\n",
      "\tgrad: tensor([-0.0219,  0.1237])\n",
      "\tparams: tensor([  5.2393, -16.5778])\n",
      "Epoch: 1873,Loss: 2.973930\n",
      "\tgrad: tensor([-0.0218,  0.1235])\n",
      "\tparams: tensor([  5.2395, -16.5791])\n",
      "Epoch: 1874,Loss: 2.973776\n",
      "\tgrad: tensor([-0.0218,  0.1233])\n",
      "\tparams: tensor([  5.2397, -16.5803])\n",
      "Epoch: 1875,Loss: 2.973618\n",
      "\tgrad: tensor([-0.0217,  0.1231])\n",
      "\tparams: tensor([  5.2400, -16.5815])\n",
      "Epoch: 1876,Loss: 2.973463\n",
      "\tgrad: tensor([-0.0217,  0.1229])\n",
      "\tparams: tensor([  5.2402, -16.5828])\n",
      "Epoch: 1877,Loss: 2.973307\n",
      "\tgrad: tensor([-0.0217,  0.1227])\n",
      "\tparams: tensor([  5.2404, -16.5840])\n",
      "Epoch: 1878,Loss: 2.973151\n",
      "\tgrad: tensor([-0.0216,  0.1224])\n",
      "\tparams: tensor([  5.2406, -16.5852])\n",
      "Epoch: 1879,Loss: 2.972996\n",
      "\tgrad: tensor([-0.0216,  0.1222])\n",
      "\tparams: tensor([  5.2408, -16.5864])\n",
      "Epoch: 1880,Loss: 2.972843\n",
      "\tgrad: tensor([-0.0215,  0.1220])\n",
      "\tparams: tensor([  5.2410, -16.5877])\n",
      "Epoch: 1881,Loss: 2.972690\n",
      "\tgrad: tensor([-0.0215,  0.1218])\n",
      "\tparams: tensor([  5.2413, -16.5889])\n",
      "Epoch: 1882,Loss: 2.972536\n",
      "\tgrad: tensor([-0.0215,  0.1216])\n",
      "\tparams: tensor([  5.2415, -16.5901])\n",
      "Epoch: 1883,Loss: 2.972383\n",
      "\tgrad: tensor([-0.0214,  0.1214])\n",
      "\tparams: tensor([  5.2417, -16.5913])\n",
      "Epoch: 1884,Loss: 2.972232\n",
      "\tgrad: tensor([-0.0214,  0.1212])\n",
      "\tparams: tensor([  5.2419, -16.5925])\n",
      "Epoch: 1885,Loss: 2.972081\n",
      "\tgrad: tensor([-0.0214,  0.1210])\n",
      "\tparams: tensor([  5.2421, -16.5937])\n",
      "Epoch: 1886,Loss: 2.971931\n",
      "\tgrad: tensor([-0.0213,  0.1208])\n",
      "\tparams: tensor([  5.2423, -16.5949])\n",
      "Epoch: 1887,Loss: 2.971780\n",
      "\tgrad: tensor([-0.0213,  0.1206])\n",
      "\tparams: tensor([  5.2425, -16.5961])\n",
      "Epoch: 1888,Loss: 2.971630\n",
      "\tgrad: tensor([-0.0213,  0.1204])\n",
      "\tparams: tensor([  5.2427, -16.5974])\n",
      "Epoch: 1889,Loss: 2.971481\n",
      "\tgrad: tensor([-0.0212,  0.1202])\n",
      "\tparams: tensor([  5.2430, -16.5986])\n",
      "Epoch: 1890,Loss: 2.971332\n",
      "\tgrad: tensor([-0.0212,  0.1200])\n",
      "\tparams: tensor([  5.2432, -16.5998])\n",
      "Epoch: 1891,Loss: 2.971184\n",
      "\tgrad: tensor([-0.0212,  0.1198])\n",
      "\tparams: tensor([  5.2434, -16.6010])\n",
      "Epoch: 1892,Loss: 2.971035\n",
      "\tgrad: tensor([-0.0211,  0.1196])\n",
      "\tparams: tensor([  5.2436, -16.6021])\n",
      "Epoch: 1893,Loss: 2.970888\n",
      "\tgrad: tensor([-0.0211,  0.1194])\n",
      "\tparams: tensor([  5.2438, -16.6033])\n",
      "Epoch: 1894,Loss: 2.970741\n",
      "\tgrad: tensor([-0.0211,  0.1192])\n",
      "\tparams: tensor([  5.2440, -16.6045])\n",
      "Epoch: 1895,Loss: 2.970596\n",
      "\tgrad: tensor([-0.0210,  0.1190])\n",
      "\tparams: tensor([  5.2442, -16.6057])\n",
      "Epoch: 1896,Loss: 2.970449\n",
      "\tgrad: tensor([-0.0210,  0.1188])\n",
      "\tparams: tensor([  5.2444, -16.6069])\n",
      "Epoch: 1897,Loss: 2.970304\n",
      "\tgrad: tensor([-0.0209,  0.1186])\n",
      "\tparams: tensor([  5.2446, -16.6081])\n",
      "Epoch: 1898,Loss: 2.970159\n",
      "\tgrad: tensor([-0.0209,  0.1183])\n",
      "\tparams: tensor([  5.2449, -16.6093])\n",
      "Epoch: 1899,Loss: 2.970016\n",
      "\tgrad: tensor([-0.0209,  0.1182])\n",
      "\tparams: tensor([  5.2451, -16.6105])\n",
      "Epoch: 1900,Loss: 2.969871\n",
      "\tgrad: tensor([-0.0208,  0.1180])\n",
      "\tparams: tensor([  5.2453, -16.6116])\n",
      "Epoch: 1901,Loss: 2.969727\n",
      "\tgrad: tensor([-0.0208,  0.1178])\n",
      "\tparams: tensor([  5.2455, -16.6128])\n",
      "Epoch: 1902,Loss: 2.969586\n",
      "\tgrad: tensor([-0.0208,  0.1175])\n",
      "\tparams: tensor([  5.2457, -16.6140])\n",
      "Epoch: 1903,Loss: 2.969443\n",
      "\tgrad: tensor([-0.0207,  0.1173])\n",
      "\tparams: tensor([  5.2459, -16.6152])\n",
      "Epoch: 1904,Loss: 2.969302\n",
      "\tgrad: tensor([-0.0207,  0.1172])\n",
      "\tparams: tensor([  5.2461, -16.6163])\n",
      "Epoch: 1905,Loss: 2.969160\n",
      "\tgrad: tensor([-0.0206,  0.1170])\n",
      "\tparams: tensor([  5.2463, -16.6175])\n",
      "Epoch: 1906,Loss: 2.969017\n",
      "\tgrad: tensor([-0.0206,  0.1168])\n",
      "\tparams: tensor([  5.2465, -16.6187])\n",
      "Epoch: 1907,Loss: 2.968879\n",
      "\tgrad: tensor([-0.0206,  0.1166])\n",
      "\tparams: tensor([  5.2467, -16.6198])\n",
      "Epoch: 1908,Loss: 2.968739\n",
      "\tgrad: tensor([-0.0205,  0.1164])\n",
      "\tparams: tensor([  5.2469, -16.6210])\n",
      "Epoch: 1909,Loss: 2.968599\n",
      "\tgrad: tensor([-0.0205,  0.1162])\n",
      "\tparams: tensor([  5.2471, -16.6222])\n",
      "Epoch: 1910,Loss: 2.968460\n",
      "\tgrad: tensor([-0.0205,  0.1160])\n",
      "\tparams: tensor([  5.2473, -16.6233])\n",
      "Epoch: 1911,Loss: 2.968321\n",
      "\tgrad: tensor([-0.0204,  0.1158])\n",
      "\tparams: tensor([  5.2475, -16.6245])\n",
      "Epoch: 1912,Loss: 2.968183\n",
      "\tgrad: tensor([-0.0204,  0.1156])\n",
      "\tparams: tensor([  5.2477, -16.6256])\n",
      "Epoch: 1913,Loss: 2.968046\n",
      "\tgrad: tensor([-0.0204,  0.1154])\n",
      "\tparams: tensor([  5.2479, -16.6268])\n",
      "Epoch: 1914,Loss: 2.967908\n",
      "\tgrad: tensor([-0.0204,  0.1152])\n",
      "\tparams: tensor([  5.2482, -16.6279])\n",
      "Epoch: 1915,Loss: 2.967772\n",
      "\tgrad: tensor([-0.0203,  0.1150])\n",
      "\tparams: tensor([  5.2484, -16.6291])\n",
      "Epoch: 1916,Loss: 2.967636\n",
      "\tgrad: tensor([-0.0203,  0.1148])\n",
      "\tparams: tensor([  5.2486, -16.6302])\n",
      "Epoch: 1917,Loss: 2.967499\n",
      "\tgrad: tensor([-0.0202,  0.1146])\n",
      "\tparams: tensor([  5.2488, -16.6314])\n",
      "Epoch: 1918,Loss: 2.967365\n",
      "\tgrad: tensor([-0.0202,  0.1144])\n",
      "\tparams: tensor([  5.2490, -16.6325])\n",
      "Epoch: 1919,Loss: 2.967230\n",
      "\tgrad: tensor([-0.0202,  0.1142])\n",
      "\tparams: tensor([  5.2492, -16.6337])\n",
      "Epoch: 1920,Loss: 2.967095\n",
      "\tgrad: tensor([-0.0202,  0.1140])\n",
      "\tparams: tensor([  5.2494, -16.6348])\n",
      "Epoch: 1921,Loss: 2.966961\n",
      "\tgrad: tensor([-0.0201,  0.1138])\n",
      "\tparams: tensor([  5.2496, -16.6360])\n",
      "Epoch: 1922,Loss: 2.966828\n",
      "\tgrad: tensor([-0.0201,  0.1136])\n",
      "\tparams: tensor([  5.2498, -16.6371])\n",
      "Epoch: 1923,Loss: 2.966693\n",
      "\tgrad: tensor([-0.0200,  0.1134])\n",
      "\tparams: tensor([  5.2500, -16.6382])\n",
      "Epoch: 1924,Loss: 2.966561\n",
      "\tgrad: tensor([-0.0200,  0.1132])\n",
      "\tparams: tensor([  5.2502, -16.6394])\n",
      "Epoch: 1925,Loss: 2.966429\n",
      "\tgrad: tensor([-0.0200,  0.1130])\n",
      "\tparams: tensor([  5.2504, -16.6405])\n",
      "Epoch: 1926,Loss: 2.966297\n",
      "\tgrad: tensor([-0.0199,  0.1128])\n",
      "\tparams: tensor([  5.2506, -16.6416])\n",
      "Epoch: 1927,Loss: 2.966168\n",
      "\tgrad: tensor([-0.0199,  0.1127])\n",
      "\tparams: tensor([  5.2508, -16.6427])\n",
      "Epoch: 1928,Loss: 2.966036\n",
      "\tgrad: tensor([-0.0199,  0.1125])\n",
      "\tparams: tensor([  5.2510, -16.6439])\n",
      "Epoch: 1929,Loss: 2.965904\n",
      "\tgrad: tensor([-0.0198,  0.1123])\n",
      "\tparams: tensor([  5.2512, -16.6450])\n",
      "Epoch: 1930,Loss: 2.965777\n",
      "\tgrad: tensor([-0.0198,  0.1121])\n",
      "\tparams: tensor([  5.2514, -16.6461])\n",
      "Epoch: 1931,Loss: 2.965647\n",
      "\tgrad: tensor([-0.0198,  0.1119])\n",
      "\tparams: tensor([  5.2516, -16.6472])\n",
      "Epoch: 1932,Loss: 2.965516\n",
      "\tgrad: tensor([-0.0197,  0.1117])\n",
      "\tparams: tensor([  5.2518, -16.6484])\n",
      "Epoch: 1933,Loss: 2.965388\n",
      "\tgrad: tensor([-0.0197,  0.1115])\n",
      "\tparams: tensor([  5.2520, -16.6495])\n",
      "Epoch: 1934,Loss: 2.965261\n",
      "\tgrad: tensor([-0.0197,  0.1113])\n",
      "\tparams: tensor([  5.2522, -16.6506])\n",
      "Epoch: 1935,Loss: 2.965131\n",
      "\tgrad: tensor([-0.0196,  0.1111])\n",
      "\tparams: tensor([  5.2523, -16.6517])\n",
      "Epoch: 1936,Loss: 2.965006\n",
      "\tgrad: tensor([-0.0196,  0.1109])\n",
      "\tparams: tensor([  5.2525, -16.6528])\n",
      "Epoch: 1937,Loss: 2.964877\n",
      "\tgrad: tensor([-0.0196,  0.1108])\n",
      "\tparams: tensor([  5.2527, -16.6539])\n",
      "Epoch: 1938,Loss: 2.964751\n",
      "\tgrad: tensor([-0.0195,  0.1106])\n",
      "\tparams: tensor([  5.2529, -16.6550])\n",
      "Epoch: 1939,Loss: 2.964625\n",
      "\tgrad: tensor([-0.0195,  0.1104])\n",
      "\tparams: tensor([  5.2531, -16.6561])\n",
      "Epoch: 1940,Loss: 2.964500\n",
      "\tgrad: tensor([-0.0195,  0.1102])\n",
      "\tparams: tensor([  5.2533, -16.6572])\n",
      "Epoch: 1941,Loss: 2.964375\n",
      "\tgrad: tensor([-0.0195,  0.1100])\n",
      "\tparams: tensor([  5.2535, -16.6583])\n",
      "Epoch: 1942,Loss: 2.964250\n",
      "\tgrad: tensor([-0.0194,  0.1098])\n",
      "\tparams: tensor([  5.2537, -16.6594])\n",
      "Epoch: 1943,Loss: 2.964126\n",
      "\tgrad: tensor([-0.0194,  0.1096])\n",
      "\tparams: tensor([  5.2539, -16.6605])\n",
      "Epoch: 1944,Loss: 2.964001\n",
      "\tgrad: tensor([-0.0194,  0.1094])\n",
      "\tparams: tensor([  5.2541, -16.6616])\n",
      "Epoch: 1945,Loss: 2.963879\n",
      "\tgrad: tensor([-0.0193,  0.1093])\n",
      "\tparams: tensor([  5.2543, -16.6627])\n",
      "Epoch: 1946,Loss: 2.963756\n",
      "\tgrad: tensor([-0.0193,  0.1091])\n",
      "\tparams: tensor([  5.2545, -16.6638])\n",
      "Epoch: 1947,Loss: 2.963632\n",
      "\tgrad: tensor([-0.0192,  0.1089])\n",
      "\tparams: tensor([  5.2547, -16.6649])\n",
      "Epoch: 1948,Loss: 2.963511\n",
      "\tgrad: tensor([-0.0192,  0.1087])\n",
      "\tparams: tensor([  5.2549, -16.6660])\n",
      "Epoch: 1949,Loss: 2.963388\n",
      "\tgrad: tensor([-0.0192,  0.1085])\n",
      "\tparams: tensor([  5.2551, -16.6671])\n",
      "Epoch: 1950,Loss: 2.963266\n",
      "\tgrad: tensor([-0.0191,  0.1083])\n",
      "\tparams: tensor([  5.2553, -16.6681])\n",
      "Epoch: 1951,Loss: 2.963149\n",
      "\tgrad: tensor([-0.0191,  0.1081])\n",
      "\tparams: tensor([  5.2554, -16.6692])\n",
      "Epoch: 1952,Loss: 2.963026\n",
      "\tgrad: tensor([-0.0191,  0.1080])\n",
      "\tparams: tensor([  5.2556, -16.6703])\n",
      "Epoch: 1953,Loss: 2.962907\n",
      "\tgrad: tensor([-0.0190,  0.1078])\n",
      "\tparams: tensor([  5.2558, -16.6714])\n",
      "Epoch: 1954,Loss: 2.962788\n",
      "\tgrad: tensor([-0.0190,  0.1076])\n",
      "\tparams: tensor([  5.2560, -16.6725])\n",
      "Epoch: 1955,Loss: 2.962667\n",
      "\tgrad: tensor([-0.0190,  0.1074])\n",
      "\tparams: tensor([  5.2562, -16.6735])\n",
      "Epoch: 1956,Loss: 2.962547\n",
      "\tgrad: tensor([-0.0189,  0.1072])\n",
      "\tparams: tensor([  5.2564, -16.6746])\n",
      "Epoch: 1957,Loss: 2.962429\n",
      "\tgrad: tensor([-0.0189,  0.1071])\n",
      "\tparams: tensor([  5.2566, -16.6757])\n",
      "Epoch: 1958,Loss: 2.962312\n",
      "\tgrad: tensor([-0.0189,  0.1069])\n",
      "\tparams: tensor([  5.2568, -16.6767])\n",
      "Epoch: 1959,Loss: 2.962195\n",
      "\tgrad: tensor([-0.0188,  0.1067])\n",
      "\tparams: tensor([  5.2570, -16.6778])\n",
      "Epoch: 1960,Loss: 2.962078\n",
      "\tgrad: tensor([-0.0188,  0.1065])\n",
      "\tparams: tensor([  5.2572, -16.6789])\n",
      "Epoch: 1961,Loss: 2.961959\n",
      "\tgrad: tensor([-0.0188,  0.1063])\n",
      "\tparams: tensor([  5.2573, -16.6799])\n",
      "Epoch: 1962,Loss: 2.961843\n",
      "\tgrad: tensor([-0.0187,  0.1062])\n",
      "\tparams: tensor([  5.2575, -16.6810])\n",
      "Epoch: 1963,Loss: 2.961728\n",
      "\tgrad: tensor([-0.0187,  0.1060])\n",
      "\tparams: tensor([  5.2577, -16.6821])\n",
      "Epoch: 1964,Loss: 2.961611\n",
      "\tgrad: tensor([-0.0187,  0.1058])\n",
      "\tparams: tensor([  5.2579, -16.6831])\n",
      "Epoch: 1965,Loss: 2.961496\n",
      "\tgrad: tensor([-0.0187,  0.1056])\n",
      "\tparams: tensor([  5.2581, -16.6842])\n",
      "Epoch: 1966,Loss: 2.961382\n",
      "\tgrad: tensor([-0.0186,  0.1054])\n",
      "\tparams: tensor([  5.2583, -16.6852])\n",
      "Epoch: 1967,Loss: 2.961267\n",
      "\tgrad: tensor([-0.0186,  0.1052])\n",
      "\tparams: tensor([  5.2585, -16.6863])\n",
      "Epoch: 1968,Loss: 2.961153\n",
      "\tgrad: tensor([-0.0186,  0.1051])\n",
      "\tparams: tensor([  5.2586, -16.6873])\n",
      "Epoch: 1969,Loss: 2.961038\n",
      "\tgrad: tensor([-0.0185,  0.1049])\n",
      "\tparams: tensor([  5.2588, -16.6884])\n",
      "Epoch: 1970,Loss: 2.960926\n",
      "\tgrad: tensor([-0.0185,  0.1047])\n",
      "\tparams: tensor([  5.2590, -16.6894])\n",
      "Epoch: 1971,Loss: 2.960813\n",
      "\tgrad: tensor([-0.0185,  0.1045])\n",
      "\tparams: tensor([  5.2592, -16.6905])\n",
      "Epoch: 1972,Loss: 2.960700\n",
      "\tgrad: tensor([-0.0184,  0.1044])\n",
      "\tparams: tensor([  5.2594, -16.6915])\n",
      "Epoch: 1973,Loss: 2.960587\n",
      "\tgrad: tensor([-0.0184,  0.1042])\n",
      "\tparams: tensor([  5.2596, -16.6926])\n",
      "Epoch: 1974,Loss: 2.960475\n",
      "\tgrad: tensor([-0.0184,  0.1040])\n",
      "\tparams: tensor([  5.2598, -16.6936])\n",
      "Epoch: 1975,Loss: 2.960365\n",
      "\tgrad: tensor([-0.0183,  0.1038])\n",
      "\tparams: tensor([  5.2599, -16.6946])\n",
      "Epoch: 1976,Loss: 2.960255\n",
      "\tgrad: tensor([-0.0183,  0.1037])\n",
      "\tparams: tensor([  5.2601, -16.6957])\n",
      "Epoch: 1977,Loss: 2.960143\n",
      "\tgrad: tensor([-0.0183,  0.1035])\n",
      "\tparams: tensor([  5.2603, -16.6967])\n",
      "Epoch: 1978,Loss: 2.960033\n",
      "\tgrad: tensor([-0.0182,  0.1033])\n",
      "\tparams: tensor([  5.2605, -16.6977])\n",
      "Epoch: 1979,Loss: 2.959923\n",
      "\tgrad: tensor([-0.0182,  0.1031])\n",
      "\tparams: tensor([  5.2607, -16.6988])\n",
      "Epoch: 1980,Loss: 2.959812\n",
      "\tgrad: tensor([-0.0182,  0.1029])\n",
      "\tparams: tensor([  5.2608, -16.6998])\n",
      "Epoch: 1981,Loss: 2.959703\n",
      "\tgrad: tensor([-0.0182,  0.1028])\n",
      "\tparams: tensor([  5.2610, -16.7008])\n",
      "Epoch: 1982,Loss: 2.959594\n",
      "\tgrad: tensor([-0.0181,  0.1026])\n",
      "\tparams: tensor([  5.2612, -16.7019])\n",
      "Epoch: 1983,Loss: 2.959486\n",
      "\tgrad: tensor([-0.0181,  0.1024])\n",
      "\tparams: tensor([  5.2614, -16.7029])\n",
      "Epoch: 1984,Loss: 2.959378\n",
      "\tgrad: tensor([-0.0181,  0.1022])\n",
      "\tparams: tensor([  5.2616, -16.7039])\n",
      "Epoch: 1985,Loss: 2.959271\n",
      "\tgrad: tensor([-0.0180,  0.1021])\n",
      "\tparams: tensor([  5.2618, -16.7049])\n",
      "Epoch: 1986,Loss: 2.959162\n",
      "\tgrad: tensor([-0.0180,  0.1019])\n",
      "\tparams: tensor([  5.2619, -16.7059])\n",
      "Epoch: 1987,Loss: 2.959055\n",
      "\tgrad: tensor([-0.0180,  0.1017])\n",
      "\tparams: tensor([  5.2621, -16.7070])\n",
      "Epoch: 1988,Loss: 2.958950\n",
      "\tgrad: tensor([-0.0179,  0.1016])\n",
      "\tparams: tensor([  5.2623, -16.7080])\n",
      "Epoch: 1989,Loss: 2.958842\n",
      "\tgrad: tensor([-0.0179,  0.1014])\n",
      "\tparams: tensor([  5.2625, -16.7090])\n",
      "Epoch: 1990,Loss: 2.958738\n",
      "\tgrad: tensor([-0.0179,  0.1012])\n",
      "\tparams: tensor([  5.2626, -16.7100])\n",
      "Epoch: 1991,Loss: 2.958632\n",
      "\tgrad: tensor([-0.0179,  0.1010])\n",
      "\tparams: tensor([  5.2628, -16.7110])\n",
      "Epoch: 1992,Loss: 2.958526\n",
      "\tgrad: tensor([-0.0178,  0.1009])\n",
      "\tparams: tensor([  5.2630, -16.7120])\n",
      "Epoch: 1993,Loss: 2.958422\n",
      "\tgrad: tensor([-0.0178,  0.1007])\n",
      "\tparams: tensor([  5.2632, -16.7130])\n",
      "Epoch: 1994,Loss: 2.958317\n",
      "\tgrad: tensor([-0.0178,  0.1005])\n",
      "\tparams: tensor([  5.2634, -16.7140])\n",
      "Epoch: 1995,Loss: 2.958212\n",
      "\tgrad: tensor([-0.0177,  0.1004])\n",
      "\tparams: tensor([  5.2635, -16.7150])\n",
      "Epoch: 1996,Loss: 2.958109\n",
      "\tgrad: tensor([-0.0177,  0.1002])\n",
      "\tparams: tensor([  5.2637, -16.7160])\n",
      "Epoch: 1997,Loss: 2.958006\n",
      "\tgrad: tensor([-0.0176,  0.1000])\n",
      "\tparams: tensor([  5.2639, -16.7170])\n",
      "Epoch: 1998,Loss: 2.957904\n",
      "\tgrad: tensor([-0.0176,  0.0998])\n",
      "\tparams: tensor([  5.2641, -16.7180])\n",
      "Epoch: 1999,Loss: 2.957801\n",
      "\tgrad: tensor([-0.0176,  0.0997])\n",
      "\tparams: tensor([  5.2642, -16.7190])\n",
      "Epoch: 2000,Loss: 2.957698\n",
      "\tgrad: tensor([-0.0176,  0.0995])\n",
      "\tparams: tensor([  5.2644, -16.7200])\n",
      "Epoch: 2001,Loss: 2.957596\n",
      "\tgrad: tensor([-0.0176,  0.0993])\n",
      "\tparams: tensor([  5.2646, -16.7210])\n",
      "Epoch: 2002,Loss: 2.957494\n",
      "\tgrad: tensor([-0.0175,  0.0992])\n",
      "\tparams: tensor([  5.2648, -16.7220])\n",
      "Epoch: 2003,Loss: 2.957393\n",
      "\tgrad: tensor([-0.0175,  0.0990])\n",
      "\tparams: tensor([  5.2649, -16.7230])\n",
      "Epoch: 2004,Loss: 2.957292\n",
      "\tgrad: tensor([-0.0174,  0.0988])\n",
      "\tparams: tensor([  5.2651, -16.7240])\n",
      "Epoch: 2005,Loss: 2.957193\n",
      "\tgrad: tensor([-0.0174,  0.0987])\n",
      "\tparams: tensor([  5.2653, -16.7250])\n",
      "Epoch: 2006,Loss: 2.957091\n",
      "\tgrad: tensor([-0.0174,  0.0985])\n",
      "\tparams: tensor([  5.2655, -16.7260])\n",
      "Epoch: 2007,Loss: 2.956992\n",
      "\tgrad: tensor([-0.0174,  0.0983])\n",
      "\tparams: tensor([  5.2656, -16.7269])\n",
      "Epoch: 2008,Loss: 2.956892\n",
      "\tgrad: tensor([-0.0173,  0.0982])\n",
      "\tparams: tensor([  5.2658, -16.7279])\n",
      "Epoch: 2009,Loss: 2.956792\n",
      "\tgrad: tensor([-0.0173,  0.0980])\n",
      "\tparams: tensor([  5.2660, -16.7289])\n",
      "Epoch: 2010,Loss: 2.956694\n",
      "\tgrad: tensor([-0.0173,  0.0978])\n",
      "\tparams: tensor([  5.2662, -16.7299])\n",
      "Epoch: 2011,Loss: 2.956595\n",
      "\tgrad: tensor([-0.0172,  0.0977])\n",
      "\tparams: tensor([  5.2663, -16.7309])\n",
      "Epoch: 2012,Loss: 2.956496\n",
      "\tgrad: tensor([-0.0172,  0.0975])\n",
      "\tparams: tensor([  5.2665, -16.7318])\n",
      "Epoch: 2013,Loss: 2.956397\n",
      "\tgrad: tensor([-0.0172,  0.0973])\n",
      "\tparams: tensor([  5.2667, -16.7328])\n",
      "Epoch: 2014,Loss: 2.956300\n",
      "\tgrad: tensor([-0.0172,  0.0972])\n",
      "\tparams: tensor([  5.2668, -16.7338])\n",
      "Epoch: 2015,Loss: 2.956204\n",
      "\tgrad: tensor([-0.0171,  0.0970])\n",
      "\tparams: tensor([  5.2670, -16.7348])\n",
      "Epoch: 2016,Loss: 2.956108\n",
      "\tgrad: tensor([-0.0171,  0.0968])\n",
      "\tparams: tensor([  5.2672, -16.7357])\n",
      "Epoch: 2017,Loss: 2.956010\n",
      "\tgrad: tensor([-0.0171,  0.0967])\n",
      "\tparams: tensor([  5.2674, -16.7367])\n",
      "Epoch: 2018,Loss: 2.955914\n",
      "\tgrad: tensor([-0.0171,  0.0965])\n",
      "\tparams: tensor([  5.2675, -16.7377])\n",
      "Epoch: 2019,Loss: 2.955817\n",
      "\tgrad: tensor([-0.0170,  0.0963])\n",
      "\tparams: tensor([  5.2677, -16.7386])\n",
      "Epoch: 2020,Loss: 2.955722\n",
      "\tgrad: tensor([-0.0170,  0.0962])\n",
      "\tparams: tensor([  5.2679, -16.7396])\n",
      "Epoch: 2021,Loss: 2.955627\n",
      "\tgrad: tensor([-0.0170,  0.0960])\n",
      "\tparams: tensor([  5.2680, -16.7405])\n",
      "Epoch: 2022,Loss: 2.955533\n",
      "\tgrad: tensor([-0.0169,  0.0959])\n",
      "\tparams: tensor([  5.2682, -16.7415])\n",
      "Epoch: 2023,Loss: 2.955436\n",
      "\tgrad: tensor([-0.0169,  0.0957])\n",
      "\tparams: tensor([  5.2684, -16.7425])\n",
      "Epoch: 2024,Loss: 2.955343\n",
      "\tgrad: tensor([-0.0169,  0.0955])\n",
      "\tparams: tensor([  5.2686, -16.7434])\n",
      "Epoch: 2025,Loss: 2.955250\n",
      "\tgrad: tensor([-0.0169,  0.0954])\n",
      "\tparams: tensor([  5.2687, -16.7444])\n",
      "Epoch: 2026,Loss: 2.955154\n",
      "\tgrad: tensor([-0.0168,  0.0952])\n",
      "\tparams: tensor([  5.2689, -16.7453])\n",
      "Epoch: 2027,Loss: 2.955062\n",
      "\tgrad: tensor([-0.0168,  0.0950])\n",
      "\tparams: tensor([  5.2691, -16.7463])\n",
      "Epoch: 2028,Loss: 2.954969\n",
      "\tgrad: tensor([-0.0168,  0.0949])\n",
      "\tparams: tensor([  5.2692, -16.7472])\n",
      "Epoch: 2029,Loss: 2.954875\n",
      "\tgrad: tensor([-0.0167,  0.0947])\n",
      "\tparams: tensor([  5.2694, -16.7482])\n",
      "Epoch: 2030,Loss: 2.954783\n",
      "\tgrad: tensor([-0.0167,  0.0946])\n",
      "\tparams: tensor([  5.2696, -16.7491])\n",
      "Epoch: 2031,Loss: 2.954691\n",
      "\tgrad: tensor([-0.0167,  0.0944])\n",
      "\tparams: tensor([  5.2697, -16.7501])\n",
      "Epoch: 2032,Loss: 2.954600\n",
      "\tgrad: tensor([-0.0167,  0.0942])\n",
      "\tparams: tensor([  5.2699, -16.7510])\n",
      "Epoch: 2033,Loss: 2.954507\n",
      "\tgrad: tensor([-0.0166,  0.0941])\n",
      "\tparams: tensor([  5.2701, -16.7519])\n",
      "Epoch: 2034,Loss: 2.954417\n",
      "\tgrad: tensor([-0.0166,  0.0939])\n",
      "\tparams: tensor([  5.2702, -16.7529])\n",
      "Epoch: 2035,Loss: 2.954326\n",
      "\tgrad: tensor([-0.0165,  0.0938])\n",
      "\tparams: tensor([  5.2704, -16.7538])\n",
      "Epoch: 2036,Loss: 2.954235\n",
      "\tgrad: tensor([-0.0165,  0.0936])\n",
      "\tparams: tensor([  5.2706, -16.7547])\n",
      "Epoch: 2037,Loss: 2.954145\n",
      "\tgrad: tensor([-0.0165,  0.0934])\n",
      "\tparams: tensor([  5.2707, -16.7557])\n",
      "Epoch: 2038,Loss: 2.954055\n",
      "\tgrad: tensor([-0.0165,  0.0933])\n",
      "\tparams: tensor([  5.2709, -16.7566])\n",
      "Epoch: 2039,Loss: 2.953966\n",
      "\tgrad: tensor([-0.0164,  0.0931])\n",
      "\tparams: tensor([  5.2710, -16.7575])\n",
      "Epoch: 2040,Loss: 2.953876\n",
      "\tgrad: tensor([-0.0164,  0.0930])\n",
      "\tparams: tensor([  5.2712, -16.7585])\n",
      "Epoch: 2041,Loss: 2.953787\n",
      "\tgrad: tensor([-0.0164,  0.0928])\n",
      "\tparams: tensor([  5.2714, -16.7594])\n",
      "Epoch: 2042,Loss: 2.953698\n",
      "\tgrad: tensor([-0.0164,  0.0926])\n",
      "\tparams: tensor([  5.2715, -16.7603])\n",
      "Epoch: 2043,Loss: 2.953610\n",
      "\tgrad: tensor([-0.0163,  0.0925])\n",
      "\tparams: tensor([  5.2717, -16.7613])\n",
      "Epoch: 2044,Loss: 2.953521\n",
      "\tgrad: tensor([-0.0163,  0.0923])\n",
      "\tparams: tensor([  5.2719, -16.7622])\n",
      "Epoch: 2045,Loss: 2.953434\n",
      "\tgrad: tensor([-0.0163,  0.0922])\n",
      "\tparams: tensor([  5.2720, -16.7631])\n",
      "Epoch: 2046,Loss: 2.953346\n",
      "\tgrad: tensor([-0.0163,  0.0920])\n",
      "\tparams: tensor([  5.2722, -16.7640])\n",
      "Epoch: 2047,Loss: 2.953259\n",
      "\tgrad: tensor([-0.0162,  0.0919])\n",
      "\tparams: tensor([  5.2724, -16.7649])\n",
      "Epoch: 2048,Loss: 2.953171\n",
      "\tgrad: tensor([-0.0162,  0.0917])\n",
      "\tparams: tensor([  5.2725, -16.7659])\n",
      "Epoch: 2049,Loss: 2.953085\n",
      "\tgrad: tensor([-0.0162,  0.0915])\n",
      "\tparams: tensor([  5.2727, -16.7668])\n",
      "Epoch: 2050,Loss: 2.953000\n",
      "\tgrad: tensor([-0.0162,  0.0914])\n",
      "\tparams: tensor([  5.2728, -16.7677])\n",
      "Epoch: 2051,Loss: 2.952913\n",
      "\tgrad: tensor([-0.0161,  0.0912])\n",
      "\tparams: tensor([  5.2730, -16.7686])\n",
      "Epoch: 2052,Loss: 2.952828\n",
      "\tgrad: tensor([-0.0161,  0.0911])\n",
      "\tparams: tensor([  5.2732, -16.7695])\n",
      "Epoch: 2053,Loss: 2.952742\n",
      "\tgrad: tensor([-0.0161,  0.0909])\n",
      "\tparams: tensor([  5.2733, -16.7704])\n",
      "Epoch: 2054,Loss: 2.952657\n",
      "\tgrad: tensor([-0.0160,  0.0908])\n",
      "\tparams: tensor([  5.2735, -16.7713])\n",
      "Epoch: 2055,Loss: 2.952571\n",
      "\tgrad: tensor([-0.0160,  0.0906])\n",
      "\tparams: tensor([  5.2736, -16.7722])\n",
      "Epoch: 2056,Loss: 2.952487\n",
      "\tgrad: tensor([-0.0160,  0.0905])\n",
      "\tparams: tensor([  5.2738, -16.7731])\n",
      "Epoch: 2057,Loss: 2.952403\n",
      "\tgrad: tensor([-0.0160,  0.0903])\n",
      "\tparams: tensor([  5.2740, -16.7740])\n",
      "Epoch: 2058,Loss: 2.952318\n",
      "\tgrad: tensor([-0.0159,  0.0902])\n",
      "\tparams: tensor([  5.2741, -16.7749])\n",
      "Epoch: 2059,Loss: 2.952235\n",
      "\tgrad: tensor([-0.0159,  0.0900])\n",
      "\tparams: tensor([  5.2743, -16.7758])\n",
      "Epoch: 2060,Loss: 2.952152\n",
      "\tgrad: tensor([-0.0159,  0.0899])\n",
      "\tparams: tensor([  5.2744, -16.7767])\n",
      "Epoch: 2061,Loss: 2.952068\n",
      "\tgrad: tensor([-0.0158,  0.0897])\n",
      "\tparams: tensor([  5.2746, -16.7776])\n",
      "Epoch: 2062,Loss: 2.951985\n",
      "\tgrad: tensor([-0.0158,  0.0895])\n",
      "\tparams: tensor([  5.2748, -16.7785])\n",
      "Epoch: 2063,Loss: 2.951902\n",
      "\tgrad: tensor([-0.0158,  0.0894])\n",
      "\tparams: tensor([  5.2749, -16.7794])\n",
      "Epoch: 2064,Loss: 2.951820\n",
      "\tgrad: tensor([-0.0158,  0.0892])\n",
      "\tparams: tensor([  5.2751, -16.7803])\n",
      "Epoch: 2065,Loss: 2.951738\n",
      "\tgrad: tensor([-0.0157,  0.0891])\n",
      "\tparams: tensor([  5.2752, -16.7812])\n",
      "Epoch: 2066,Loss: 2.951656\n",
      "\tgrad: tensor([-0.0157,  0.0889])\n",
      "\tparams: tensor([  5.2754, -16.7821])\n",
      "Epoch: 2067,Loss: 2.951576\n",
      "\tgrad: tensor([-0.0157,  0.0888])\n",
      "\tparams: tensor([  5.2755, -16.7830])\n",
      "Epoch: 2068,Loss: 2.951494\n",
      "\tgrad: tensor([-0.0157,  0.0886])\n",
      "\tparams: tensor([  5.2757, -16.7839])\n",
      "Epoch: 2069,Loss: 2.951413\n",
      "\tgrad: tensor([-0.0157,  0.0885])\n",
      "\tparams: tensor([  5.2759, -16.7848])\n",
      "Epoch: 2070,Loss: 2.951333\n",
      "\tgrad: tensor([-0.0156,  0.0883])\n",
      "\tparams: tensor([  5.2760, -16.7856])\n",
      "Epoch: 2071,Loss: 2.951252\n",
      "\tgrad: tensor([-0.0156,  0.0882])\n",
      "\tparams: tensor([  5.2762, -16.7865])\n",
      "Epoch: 2072,Loss: 2.951171\n",
      "\tgrad: tensor([-0.0155,  0.0880])\n",
      "\tparams: tensor([  5.2763, -16.7874])\n",
      "Epoch: 2073,Loss: 2.951093\n",
      "\tgrad: tensor([-0.0155,  0.0879])\n",
      "\tparams: tensor([  5.2765, -16.7883])\n",
      "Epoch: 2074,Loss: 2.951012\n",
      "\tgrad: tensor([-0.0155,  0.0877])\n",
      "\tparams: tensor([  5.2766, -16.7892])\n",
      "Epoch: 2075,Loss: 2.950932\n",
      "\tgrad: tensor([-0.0155,  0.0876])\n",
      "\tparams: tensor([  5.2768, -16.7900])\n",
      "Epoch: 2076,Loss: 2.950853\n",
      "\tgrad: tensor([-0.0154,  0.0874])\n",
      "\tparams: tensor([  5.2769, -16.7909])\n",
      "Epoch: 2077,Loss: 2.950774\n",
      "\tgrad: tensor([-0.0154,  0.0873])\n",
      "\tparams: tensor([  5.2771, -16.7918])\n",
      "Epoch: 2078,Loss: 2.950697\n",
      "\tgrad: tensor([-0.0154,  0.0871])\n",
      "\tparams: tensor([  5.2772, -16.7927])\n",
      "Epoch: 2079,Loss: 2.950618\n",
      "\tgrad: tensor([-0.0154,  0.0870])\n",
      "\tparams: tensor([  5.2774, -16.7935])\n",
      "Epoch: 2080,Loss: 2.950540\n",
      "\tgrad: tensor([-0.0154,  0.0868])\n",
      "\tparams: tensor([  5.2776, -16.7944])\n",
      "Epoch: 2081,Loss: 2.950463\n",
      "\tgrad: tensor([-0.0153,  0.0867])\n",
      "\tparams: tensor([  5.2777, -16.7953])\n",
      "Epoch: 2082,Loss: 2.950385\n",
      "\tgrad: tensor([-0.0153,  0.0866])\n",
      "\tparams: tensor([  5.2779, -16.7961])\n",
      "Epoch: 2083,Loss: 2.950308\n",
      "\tgrad: tensor([-0.0153,  0.0864])\n",
      "\tparams: tensor([  5.2780, -16.7970])\n",
      "Epoch: 2084,Loss: 2.950231\n",
      "\tgrad: tensor([-0.0152,  0.0863])\n",
      "\tparams: tensor([  5.2782, -16.7979])\n",
      "Epoch: 2085,Loss: 2.950154\n",
      "\tgrad: tensor([-0.0152,  0.0861])\n",
      "\tparams: tensor([  5.2783, -16.7987])\n",
      "Epoch: 2086,Loss: 2.950078\n",
      "\tgrad: tensor([-0.0152,  0.0860])\n",
      "\tparams: tensor([  5.2785, -16.7996])\n",
      "Epoch: 2087,Loss: 2.950003\n",
      "\tgrad: tensor([-0.0152,  0.0858])\n",
      "\tparams: tensor([  5.2786, -16.8004])\n",
      "Epoch: 2088,Loss: 2.949925\n",
      "\tgrad: tensor([-0.0152,  0.0857])\n",
      "\tparams: tensor([  5.2788, -16.8013])\n",
      "Epoch: 2089,Loss: 2.949850\n",
      "\tgrad: tensor([-0.0151,  0.0855])\n",
      "\tparams: tensor([  5.2789, -16.8021])\n",
      "Epoch: 2090,Loss: 2.949776\n",
      "\tgrad: tensor([-0.0151,  0.0854])\n",
      "\tparams: tensor([  5.2791, -16.8030])\n",
      "Epoch: 2091,Loss: 2.949699\n",
      "\tgrad: tensor([-0.0151,  0.0852])\n",
      "\tparams: tensor([  5.2792, -16.8039])\n",
      "Epoch: 2092,Loss: 2.949626\n",
      "\tgrad: tensor([-0.0150,  0.0851])\n",
      "\tparams: tensor([  5.2794, -16.8047])\n",
      "Epoch: 2093,Loss: 2.949550\n",
      "\tgrad: tensor([-0.0150,  0.0850])\n",
      "\tparams: tensor([  5.2795, -16.8056])\n",
      "Epoch: 2094,Loss: 2.949476\n",
      "\tgrad: tensor([-0.0150,  0.0848])\n",
      "\tparams: tensor([  5.2797, -16.8064])\n",
      "Epoch: 2095,Loss: 2.949401\n",
      "\tgrad: tensor([-0.0149,  0.0847])\n",
      "\tparams: tensor([  5.2798, -16.8072])\n",
      "Epoch: 2096,Loss: 2.949328\n",
      "\tgrad: tensor([-0.0150,  0.0845])\n",
      "\tparams: tensor([  5.2800, -16.8081])\n",
      "Epoch: 2097,Loss: 2.949254\n",
      "\tgrad: tensor([-0.0149,  0.0844])\n",
      "\tparams: tensor([  5.2801, -16.8089])\n",
      "Epoch: 2098,Loss: 2.949182\n",
      "\tgrad: tensor([-0.0149,  0.0842])\n",
      "\tparams: tensor([  5.2803, -16.8098])\n",
      "Epoch: 2099,Loss: 2.949108\n",
      "\tgrad: tensor([-0.0149,  0.0841])\n",
      "\tparams: tensor([  5.2804, -16.8106])\n",
      "Epoch: 2100,Loss: 2.949035\n",
      "\tgrad: tensor([-0.0148,  0.0839])\n",
      "\tparams: tensor([  5.2806, -16.8115])\n",
      "Epoch: 2101,Loss: 2.948962\n",
      "\tgrad: tensor([-0.0148,  0.0838])\n",
      "\tparams: tensor([  5.2807, -16.8123])\n",
      "Epoch: 2102,Loss: 2.948890\n",
      "\tgrad: tensor([-0.0148,  0.0837])\n",
      "\tparams: tensor([  5.2809, -16.8131])\n",
      "Epoch: 2103,Loss: 2.948818\n",
      "\tgrad: tensor([-0.0148,  0.0835])\n",
      "\tparams: tensor([  5.2810, -16.8140])\n",
      "Epoch: 2104,Loss: 2.948745\n",
      "\tgrad: tensor([-0.0148,  0.0834])\n",
      "\tparams: tensor([  5.2812, -16.8148])\n",
      "Epoch: 2105,Loss: 2.948675\n",
      "\tgrad: tensor([-0.0147,  0.0832])\n",
      "\tparams: tensor([  5.2813, -16.8156])\n",
      "Epoch: 2106,Loss: 2.948602\n",
      "\tgrad: tensor([-0.0147,  0.0831])\n",
      "\tparams: tensor([  5.2815, -16.8165])\n",
      "Epoch: 2107,Loss: 2.948532\n",
      "\tgrad: tensor([-0.0146,  0.0830])\n",
      "\tparams: tensor([  5.2816, -16.8173])\n",
      "Epoch: 2108,Loss: 2.948462\n",
      "\tgrad: tensor([-0.0146,  0.0828])\n",
      "\tparams: tensor([  5.2817, -16.8181])\n",
      "Epoch: 2109,Loss: 2.948391\n",
      "\tgrad: tensor([-0.0146,  0.0827])\n",
      "\tparams: tensor([  5.2819, -16.8189])\n",
      "Epoch: 2110,Loss: 2.948321\n",
      "\tgrad: tensor([-0.0146,  0.0825])\n",
      "\tparams: tensor([  5.2820, -16.8198])\n",
      "Epoch: 2111,Loss: 2.948250\n",
      "\tgrad: tensor([-0.0145,  0.0824])\n",
      "\tparams: tensor([  5.2822, -16.8206])\n",
      "Epoch: 2112,Loss: 2.948181\n",
      "\tgrad: tensor([-0.0145,  0.0823])\n",
      "\tparams: tensor([  5.2823, -16.8214])\n",
      "Epoch: 2113,Loss: 2.948109\n",
      "\tgrad: tensor([-0.0145,  0.0821])\n",
      "\tparams: tensor([  5.2825, -16.8222])\n",
      "Epoch: 2114,Loss: 2.948041\n",
      "\tgrad: tensor([-0.0145,  0.0820])\n",
      "\tparams: tensor([  5.2826, -16.8231])\n",
      "Epoch: 2115,Loss: 2.947971\n",
      "\tgrad: tensor([-0.0144,  0.0818])\n",
      "\tparams: tensor([  5.2828, -16.8239])\n",
      "Epoch: 2116,Loss: 2.947902\n",
      "\tgrad: tensor([-0.0144,  0.0817])\n",
      "\tparams: tensor([  5.2829, -16.8247])\n",
      "Epoch: 2117,Loss: 2.947833\n",
      "\tgrad: tensor([-0.0144,  0.0816])\n",
      "\tparams: tensor([  5.2831, -16.8255])\n",
      "Epoch: 2118,Loss: 2.947765\n",
      "\tgrad: tensor([-0.0144,  0.0814])\n",
      "\tparams: tensor([  5.2832, -16.8263])\n",
      "Epoch: 2119,Loss: 2.947696\n",
      "\tgrad: tensor([-0.0144,  0.0813])\n",
      "\tparams: tensor([  5.2833, -16.8271])\n",
      "Epoch: 2120,Loss: 2.947628\n",
      "\tgrad: tensor([-0.0143,  0.0811])\n",
      "\tparams: tensor([  5.2835, -16.8280])\n",
      "Epoch: 2121,Loss: 2.947560\n",
      "\tgrad: tensor([-0.0143,  0.0810])\n",
      "\tparams: tensor([  5.2836, -16.8288])\n",
      "Epoch: 2122,Loss: 2.947494\n",
      "\tgrad: tensor([-0.0143,  0.0809])\n",
      "\tparams: tensor([  5.2838, -16.8296])\n",
      "Epoch: 2123,Loss: 2.947426\n",
      "\tgrad: tensor([-0.0143,  0.0807])\n",
      "\tparams: tensor([  5.2839, -16.8304])\n",
      "Epoch: 2124,Loss: 2.947357\n",
      "\tgrad: tensor([-0.0142,  0.0806])\n",
      "\tparams: tensor([  5.2841, -16.8312])\n",
      "Epoch: 2125,Loss: 2.947293\n",
      "\tgrad: tensor([-0.0142,  0.0805])\n",
      "\tparams: tensor([  5.2842, -16.8320])\n",
      "Epoch: 2126,Loss: 2.947225\n",
      "\tgrad: tensor([-0.0142,  0.0803])\n",
      "\tparams: tensor([  5.2843, -16.8328])\n",
      "Epoch: 2127,Loss: 2.947158\n",
      "\tgrad: tensor([-0.0142,  0.0802])\n",
      "\tparams: tensor([  5.2845, -16.8336])\n",
      "Epoch: 2128,Loss: 2.947092\n",
      "\tgrad: tensor([-0.0141,  0.0800])\n",
      "\tparams: tensor([  5.2846, -16.8344])\n",
      "Epoch: 2129,Loss: 2.947026\n",
      "\tgrad: tensor([-0.0141,  0.0799])\n",
      "\tparams: tensor([  5.2848, -16.8352])\n",
      "Epoch: 2130,Loss: 2.946960\n",
      "\tgrad: tensor([-0.0141,  0.0798])\n",
      "\tparams: tensor([  5.2849, -16.8360])\n",
      "Epoch: 2131,Loss: 2.946895\n",
      "\tgrad: tensor([-0.0141,  0.0796])\n",
      "\tparams: tensor([  5.2850, -16.8368])\n",
      "Epoch: 2132,Loss: 2.946830\n",
      "\tgrad: tensor([-0.0141,  0.0795])\n",
      "\tparams: tensor([  5.2852, -16.8376])\n",
      "Epoch: 2133,Loss: 2.946764\n",
      "\tgrad: tensor([-0.0140,  0.0794])\n",
      "\tparams: tensor([  5.2853, -16.8384])\n",
      "Epoch: 2134,Loss: 2.946700\n",
      "\tgrad: tensor([-0.0140,  0.0792])\n",
      "\tparams: tensor([  5.2855, -16.8392])\n",
      "Epoch: 2135,Loss: 2.946635\n",
      "\tgrad: tensor([-0.0140,  0.0791])\n",
      "\tparams: tensor([  5.2856, -16.8400])\n",
      "Epoch: 2136,Loss: 2.946571\n",
      "\tgrad: tensor([-0.0139,  0.0790])\n",
      "\tparams: tensor([  5.2857, -16.8407])\n",
      "Epoch: 2137,Loss: 2.946507\n",
      "\tgrad: tensor([-0.0139,  0.0788])\n",
      "\tparams: tensor([  5.2859, -16.8415])\n",
      "Epoch: 2138,Loss: 2.946442\n",
      "\tgrad: tensor([-0.0139,  0.0787])\n",
      "\tparams: tensor([  5.2860, -16.8423])\n",
      "Epoch: 2139,Loss: 2.946378\n",
      "\tgrad: tensor([-0.0139,  0.0786])\n",
      "\tparams: tensor([  5.2862, -16.8431])\n",
      "Epoch: 2140,Loss: 2.946314\n",
      "\tgrad: tensor([-0.0138,  0.0784])\n",
      "\tparams: tensor([  5.2863, -16.8439])\n",
      "Epoch: 2141,Loss: 2.946251\n",
      "\tgrad: tensor([-0.0138,  0.0783])\n",
      "\tparams: tensor([  5.2864, -16.8447])\n",
      "Epoch: 2142,Loss: 2.946189\n",
      "\tgrad: tensor([-0.0138,  0.0782])\n",
      "\tparams: tensor([  5.2866, -16.8455])\n",
      "Epoch: 2143,Loss: 2.946126\n",
      "\tgrad: tensor([-0.0138,  0.0780])\n",
      "\tparams: tensor([  5.2867, -16.8462])\n",
      "Epoch: 2144,Loss: 2.946063\n",
      "\tgrad: tensor([-0.0138,  0.0779])\n",
      "\tparams: tensor([  5.2869, -16.8470])\n",
      "Epoch: 2145,Loss: 2.946001\n",
      "\tgrad: tensor([-0.0137,  0.0778])\n",
      "\tparams: tensor([  5.2870, -16.8478])\n",
      "Epoch: 2146,Loss: 2.945937\n",
      "\tgrad: tensor([-0.0137,  0.0776])\n",
      "\tparams: tensor([  5.2871, -16.8486])\n",
      "Epoch: 2147,Loss: 2.945876\n",
      "\tgrad: tensor([-0.0137,  0.0775])\n",
      "\tparams: tensor([  5.2873, -16.8493])\n",
      "Epoch: 2148,Loss: 2.945815\n",
      "\tgrad: tensor([-0.0137,  0.0774])\n",
      "\tparams: tensor([  5.2874, -16.8501])\n",
      "Epoch: 2149,Loss: 2.945753\n",
      "\tgrad: tensor([-0.0136,  0.0772])\n",
      "\tparams: tensor([  5.2875, -16.8509])\n",
      "Epoch: 2150,Loss: 2.945690\n",
      "\tgrad: tensor([-0.0136,  0.0771])\n",
      "\tparams: tensor([  5.2877, -16.8517])\n",
      "Epoch: 2151,Loss: 2.945630\n",
      "\tgrad: tensor([-0.0136,  0.0770])\n",
      "\tparams: tensor([  5.2878, -16.8524])\n",
      "Epoch: 2152,Loss: 2.945567\n",
      "\tgrad: tensor([-0.0136,  0.0768])\n",
      "\tparams: tensor([  5.2879, -16.8532])\n",
      "Epoch: 2153,Loss: 2.945508\n",
      "\tgrad: tensor([-0.0135,  0.0767])\n",
      "\tparams: tensor([  5.2881, -16.8540])\n",
      "Epoch: 2154,Loss: 2.945447\n",
      "\tgrad: tensor([-0.0135,  0.0766])\n",
      "\tparams: tensor([  5.2882, -16.8547])\n",
      "Epoch: 2155,Loss: 2.945385\n",
      "\tgrad: tensor([-0.0135,  0.0765])\n",
      "\tparams: tensor([  5.2884, -16.8555])\n",
      "Epoch: 2156,Loss: 2.945325\n",
      "\tgrad: tensor([-0.0135,  0.0763])\n",
      "\tparams: tensor([  5.2885, -16.8563])\n",
      "Epoch: 2157,Loss: 2.945267\n",
      "\tgrad: tensor([-0.0135,  0.0762])\n",
      "\tparams: tensor([  5.2886, -16.8570])\n",
      "Epoch: 2158,Loss: 2.945206\n",
      "\tgrad: tensor([-0.0134,  0.0761])\n",
      "\tparams: tensor([  5.2888, -16.8578])\n",
      "Epoch: 2159,Loss: 2.945146\n",
      "\tgrad: tensor([-0.0134,  0.0759])\n",
      "\tparams: tensor([  5.2889, -16.8585])\n",
      "Epoch: 2160,Loss: 2.945088\n",
      "\tgrad: tensor([-0.0134,  0.0758])\n",
      "\tparams: tensor([  5.2890, -16.8593])\n",
      "Epoch: 2161,Loss: 2.945028\n",
      "\tgrad: tensor([-0.0134,  0.0757])\n",
      "\tparams: tensor([  5.2892, -16.8601])\n",
      "Epoch: 2162,Loss: 2.944969\n",
      "\tgrad: tensor([-0.0133,  0.0755])\n",
      "\tparams: tensor([  5.2893, -16.8608])\n",
      "Epoch: 2163,Loss: 2.944911\n",
      "\tgrad: tensor([-0.0133,  0.0754])\n",
      "\tparams: tensor([  5.2894, -16.8616])\n",
      "Epoch: 2164,Loss: 2.944852\n",
      "\tgrad: tensor([-0.0133,  0.0753])\n",
      "\tparams: tensor([  5.2896, -16.8623])\n",
      "Epoch: 2165,Loss: 2.944792\n",
      "\tgrad: tensor([-0.0133,  0.0752])\n",
      "\tparams: tensor([  5.2897, -16.8631])\n",
      "Epoch: 2166,Loss: 2.944736\n",
      "\tgrad: tensor([-0.0133,  0.0750])\n",
      "\tparams: tensor([  5.2898, -16.8638])\n",
      "Epoch: 2167,Loss: 2.944678\n",
      "\tgrad: tensor([-0.0132,  0.0749])\n",
      "\tparams: tensor([  5.2900, -16.8646])\n",
      "Epoch: 2168,Loss: 2.944619\n",
      "\tgrad: tensor([-0.0132,  0.0748])\n",
      "\tparams: tensor([  5.2901, -16.8653])\n",
      "Epoch: 2169,Loss: 2.944562\n",
      "\tgrad: tensor([-0.0132,  0.0747])\n",
      "\tparams: tensor([  5.2902, -16.8661])\n",
      "Epoch: 2170,Loss: 2.944504\n",
      "\tgrad: tensor([-0.0132,  0.0745])\n",
      "\tparams: tensor([  5.2903, -16.8668])\n",
      "Epoch: 2171,Loss: 2.944447\n",
      "\tgrad: tensor([-0.0132,  0.0744])\n",
      "\tparams: tensor([  5.2905, -16.8676])\n",
      "Epoch: 2172,Loss: 2.944391\n",
      "\tgrad: tensor([-0.0131,  0.0743])\n",
      "\tparams: tensor([  5.2906, -16.8683])\n",
      "Epoch: 2173,Loss: 2.944332\n",
      "\tgrad: tensor([-0.0131,  0.0742])\n",
      "\tparams: tensor([  5.2907, -16.8690])\n",
      "Epoch: 2174,Loss: 2.944276\n",
      "\tgrad: tensor([-0.0131,  0.0740])\n",
      "\tparams: tensor([  5.2909, -16.8698])\n",
      "Epoch: 2175,Loss: 2.944220\n",
      "\tgrad: tensor([-0.0131,  0.0739])\n",
      "\tparams: tensor([  5.2910, -16.8705])\n",
      "Epoch: 2176,Loss: 2.944164\n",
      "\tgrad: tensor([-0.0130,  0.0738])\n",
      "\tparams: tensor([  5.2911, -16.8713])\n",
      "Epoch: 2177,Loss: 2.944108\n",
      "\tgrad: tensor([-0.0130,  0.0736])\n",
      "\tparams: tensor([  5.2913, -16.8720])\n",
      "Epoch: 2178,Loss: 2.944053\n",
      "\tgrad: tensor([-0.0130,  0.0735])\n",
      "\tparams: tensor([  5.2914, -16.8727])\n",
      "Epoch: 2179,Loss: 2.943996\n",
      "\tgrad: tensor([-0.0130,  0.0734])\n",
      "\tparams: tensor([  5.2915, -16.8735])\n",
      "Epoch: 2180,Loss: 2.943941\n",
      "\tgrad: tensor([-0.0129,  0.0733])\n",
      "\tparams: tensor([  5.2917, -16.8742])\n",
      "Epoch: 2181,Loss: 2.943887\n",
      "\tgrad: tensor([-0.0129,  0.0731])\n",
      "\tparams: tensor([  5.2918, -16.8749])\n",
      "Epoch: 2182,Loss: 2.943831\n",
      "\tgrad: tensor([-0.0129,  0.0730])\n",
      "\tparams: tensor([  5.2919, -16.8757])\n",
      "Epoch: 2183,Loss: 2.943776\n",
      "\tgrad: tensor([-0.0129,  0.0729])\n",
      "\tparams: tensor([  5.2920, -16.8764])\n",
      "Epoch: 2184,Loss: 2.943721\n",
      "\tgrad: tensor([-0.0129,  0.0728])\n",
      "\tparams: tensor([  5.2922, -16.8771])\n",
      "Epoch: 2185,Loss: 2.943666\n",
      "\tgrad: tensor([-0.0128,  0.0727])\n",
      "\tparams: tensor([  5.2923, -16.8778])\n",
      "Epoch: 2186,Loss: 2.943613\n",
      "\tgrad: tensor([-0.0128,  0.0725])\n",
      "\tparams: tensor([  5.2924, -16.8786])\n",
      "Epoch: 2187,Loss: 2.943558\n",
      "\tgrad: tensor([-0.0128,  0.0724])\n",
      "\tparams: tensor([  5.2926, -16.8793])\n",
      "Epoch: 2188,Loss: 2.943503\n",
      "\tgrad: tensor([-0.0128,  0.0723])\n",
      "\tparams: tensor([  5.2927, -16.8800])\n",
      "Epoch: 2189,Loss: 2.943451\n",
      "\tgrad: tensor([-0.0127,  0.0722])\n",
      "\tparams: tensor([  5.2928, -16.8807])\n",
      "Epoch: 2190,Loss: 2.943395\n",
      "\tgrad: tensor([-0.0127,  0.0720])\n",
      "\tparams: tensor([  5.2929, -16.8815])\n",
      "Epoch: 2191,Loss: 2.943343\n",
      "\tgrad: tensor([-0.0127,  0.0719])\n",
      "\tparams: tensor([  5.2931, -16.8822])\n",
      "Epoch: 2192,Loss: 2.943290\n",
      "\tgrad: tensor([-0.0127,  0.0718])\n",
      "\tparams: tensor([  5.2932, -16.8829])\n",
      "Epoch: 2193,Loss: 2.943235\n",
      "\tgrad: tensor([-0.0127,  0.0717])\n",
      "\tparams: tensor([  5.2933, -16.8836])\n",
      "Epoch: 2194,Loss: 2.943183\n",
      "\tgrad: tensor([-0.0126,  0.0715])\n",
      "\tparams: tensor([  5.2934, -16.8843])\n",
      "Epoch: 2195,Loss: 2.943130\n",
      "\tgrad: tensor([-0.0126,  0.0714])\n",
      "\tparams: tensor([  5.2936, -16.8850])\n",
      "Epoch: 2196,Loss: 2.943079\n",
      "\tgrad: tensor([-0.0126,  0.0713])\n",
      "\tparams: tensor([  5.2937, -16.8857])\n",
      "Epoch: 2197,Loss: 2.943027\n",
      "\tgrad: tensor([-0.0126,  0.0712])\n",
      "\tparams: tensor([  5.2938, -16.8865])\n",
      "Epoch: 2198,Loss: 2.942973\n",
      "\tgrad: tensor([-0.0126,  0.0711])\n",
      "\tparams: tensor([  5.2939, -16.8872])\n",
      "Epoch: 2199,Loss: 2.942922\n",
      "\tgrad: tensor([-0.0125,  0.0709])\n",
      "\tparams: tensor([  5.2941, -16.8879])\n",
      "Epoch: 2200,Loss: 2.942870\n",
      "\tgrad: tensor([-0.0125,  0.0708])\n",
      "\tparams: tensor([  5.2942, -16.8886])\n",
      "Epoch: 2201,Loss: 2.942818\n",
      "\tgrad: tensor([-0.0125,  0.0707])\n",
      "\tparams: tensor([  5.2943, -16.8893])\n",
      "Epoch: 2202,Loss: 2.942766\n",
      "\tgrad: tensor([-0.0125,  0.0706])\n",
      "\tparams: tensor([  5.2944, -16.8900])\n",
      "Epoch: 2203,Loss: 2.942714\n",
      "\tgrad: tensor([-0.0124,  0.0705])\n",
      "\tparams: tensor([  5.2946, -16.8907])\n",
      "Epoch: 2204,Loss: 2.942665\n",
      "\tgrad: tensor([-0.0124,  0.0703])\n",
      "\tparams: tensor([  5.2947, -16.8914])\n",
      "Epoch: 2205,Loss: 2.942612\n",
      "\tgrad: tensor([-0.0124,  0.0702])\n",
      "\tparams: tensor([  5.2948, -16.8921])\n",
      "Epoch: 2206,Loss: 2.942564\n",
      "\tgrad: tensor([-0.0124,  0.0701])\n",
      "\tparams: tensor([  5.2949, -16.8928])\n",
      "Epoch: 2207,Loss: 2.942510\n",
      "\tgrad: tensor([-0.0124,  0.0700])\n",
      "\tparams: tensor([  5.2951, -16.8935])\n",
      "Epoch: 2208,Loss: 2.942461\n",
      "\tgrad: tensor([-0.0123,  0.0699])\n",
      "\tparams: tensor([  5.2952, -16.8942])\n",
      "Epoch: 2209,Loss: 2.942411\n",
      "\tgrad: tensor([-0.0123,  0.0697])\n",
      "\tparams: tensor([  5.2953, -16.8949])\n",
      "Epoch: 2210,Loss: 2.942361\n",
      "\tgrad: tensor([-0.0123,  0.0696])\n",
      "\tparams: tensor([  5.2954, -16.8956])\n",
      "Epoch: 2211,Loss: 2.942310\n",
      "\tgrad: tensor([-0.0123,  0.0695])\n",
      "\tparams: tensor([  5.2956, -16.8963])\n",
      "Epoch: 2212,Loss: 2.942261\n",
      "\tgrad: tensor([-0.0122,  0.0694])\n",
      "\tparams: tensor([  5.2957, -16.8970])\n",
      "Epoch: 2213,Loss: 2.942211\n",
      "\tgrad: tensor([-0.0122,  0.0693])\n",
      "\tparams: tensor([  5.2958, -16.8977])\n",
      "Epoch: 2214,Loss: 2.942162\n",
      "\tgrad: tensor([-0.0122,  0.0692])\n",
      "\tparams: tensor([  5.2959, -16.8984])\n",
      "Epoch: 2215,Loss: 2.942112\n",
      "\tgrad: tensor([-0.0122,  0.0690])\n",
      "\tparams: tensor([  5.2960, -16.8991])\n",
      "Epoch: 2216,Loss: 2.942062\n",
      "\tgrad: tensor([-0.0122,  0.0689])\n",
      "\tparams: tensor([  5.2962, -16.8998])\n",
      "Epoch: 2217,Loss: 2.942014\n",
      "\tgrad: tensor([-0.0122,  0.0688])\n",
      "\tparams: tensor([  5.2963, -16.9004])\n",
      "Epoch: 2218,Loss: 2.941965\n",
      "\tgrad: tensor([-0.0121,  0.0687])\n",
      "\tparams: tensor([  5.2964, -16.9011])\n",
      "Epoch: 2219,Loss: 2.941918\n",
      "\tgrad: tensor([-0.0121,  0.0686])\n",
      "\tparams: tensor([  5.2965, -16.9018])\n",
      "Epoch: 2220,Loss: 2.941868\n",
      "\tgrad: tensor([-0.0121,  0.0685])\n",
      "\tparams: tensor([  5.2967, -16.9025])\n",
      "Epoch: 2221,Loss: 2.941821\n",
      "\tgrad: tensor([-0.0121,  0.0683])\n",
      "\tparams: tensor([  5.2968, -16.9032])\n",
      "Epoch: 2222,Loss: 2.941773\n",
      "\tgrad: tensor([-0.0120,  0.0682])\n",
      "\tparams: tensor([  5.2969, -16.9039])\n",
      "Epoch: 2223,Loss: 2.941724\n",
      "\tgrad: tensor([-0.0120,  0.0681])\n",
      "\tparams: tensor([  5.2970, -16.9046])\n",
      "Epoch: 2224,Loss: 2.941677\n",
      "\tgrad: tensor([-0.0120,  0.0680])\n",
      "\tparams: tensor([  5.2971, -16.9052])\n",
      "Epoch: 2225,Loss: 2.941629\n",
      "\tgrad: tensor([-0.0120,  0.0679])\n",
      "\tparams: tensor([  5.2973, -16.9059])\n",
      "Epoch: 2226,Loss: 2.941582\n",
      "\tgrad: tensor([-0.0120,  0.0678])\n",
      "\tparams: tensor([  5.2974, -16.9066])\n",
      "Epoch: 2227,Loss: 2.941534\n",
      "\tgrad: tensor([-0.0119,  0.0676])\n",
      "\tparams: tensor([  5.2975, -16.9073])\n",
      "Epoch: 2228,Loss: 2.941488\n",
      "\tgrad: tensor([-0.0119,  0.0675])\n",
      "\tparams: tensor([  5.2976, -16.9079])\n",
      "Epoch: 2229,Loss: 2.941440\n",
      "\tgrad: tensor([-0.0119,  0.0674])\n",
      "\tparams: tensor([  5.2977, -16.9086])\n",
      "Epoch: 2230,Loss: 2.941393\n",
      "\tgrad: tensor([-0.0119,  0.0673])\n",
      "\tparams: tensor([  5.2979, -16.9093])\n",
      "Epoch: 2231,Loss: 2.941346\n",
      "\tgrad: tensor([-0.0119,  0.0672])\n",
      "\tparams: tensor([  5.2980, -16.9100])\n",
      "Epoch: 2232,Loss: 2.941299\n",
      "\tgrad: tensor([-0.0118,  0.0671])\n",
      "\tparams: tensor([  5.2981, -16.9106])\n",
      "Epoch: 2233,Loss: 2.941253\n",
      "\tgrad: tensor([-0.0118,  0.0670])\n",
      "\tparams: tensor([  5.2982, -16.9113])\n",
      "Epoch: 2234,Loss: 2.941206\n",
      "\tgrad: tensor([-0.0118,  0.0668])\n",
      "\tparams: tensor([  5.2983, -16.9120])\n",
      "Epoch: 2235,Loss: 2.941163\n",
      "\tgrad: tensor([-0.0118,  0.0667])\n",
      "\tparams: tensor([  5.2984, -16.9126])\n",
      "Epoch: 2236,Loss: 2.941116\n",
      "\tgrad: tensor([-0.0118,  0.0666])\n",
      "\tparams: tensor([  5.2986, -16.9133])\n",
      "Epoch: 2237,Loss: 2.941070\n",
      "\tgrad: tensor([-0.0117,  0.0665])\n",
      "\tparams: tensor([  5.2987, -16.9140])\n",
      "Epoch: 2238,Loss: 2.941025\n",
      "\tgrad: tensor([-0.0117,  0.0664])\n",
      "\tparams: tensor([  5.2988, -16.9146])\n",
      "Epoch: 2239,Loss: 2.940979\n",
      "\tgrad: tensor([-0.0117,  0.0663])\n",
      "\tparams: tensor([  5.2989, -16.9153])\n",
      "Epoch: 2240,Loss: 2.940933\n",
      "\tgrad: tensor([-0.0117,  0.0662])\n",
      "\tparams: tensor([  5.2990, -16.9160])\n",
      "Epoch: 2241,Loss: 2.940890\n",
      "\tgrad: tensor([-0.0117,  0.0661])\n",
      "\tparams: tensor([  5.2991, -16.9166])\n",
      "Epoch: 2242,Loss: 2.940844\n",
      "\tgrad: tensor([-0.0117,  0.0659])\n",
      "\tparams: tensor([  5.2993, -16.9173])\n",
      "Epoch: 2243,Loss: 2.940798\n",
      "\tgrad: tensor([-0.0116,  0.0658])\n",
      "\tparams: tensor([  5.2994, -16.9179])\n",
      "Epoch: 2244,Loss: 2.940753\n",
      "\tgrad: tensor([-0.0116,  0.0657])\n",
      "\tparams: tensor([  5.2995, -16.9186])\n",
      "Epoch: 2245,Loss: 2.940711\n",
      "\tgrad: tensor([-0.0116,  0.0656])\n",
      "\tparams: tensor([  5.2996, -16.9192])\n",
      "Epoch: 2246,Loss: 2.940666\n",
      "\tgrad: tensor([-0.0116,  0.0655])\n",
      "\tparams: tensor([  5.2997, -16.9199])\n",
      "Epoch: 2247,Loss: 2.940621\n",
      "\tgrad: tensor([-0.0115,  0.0654])\n",
      "\tparams: tensor([  5.2998, -16.9206])\n",
      "Epoch: 2248,Loss: 2.940576\n",
      "\tgrad: tensor([-0.0115,  0.0653])\n",
      "\tparams: tensor([  5.3000, -16.9212])\n",
      "Epoch: 2249,Loss: 2.940533\n",
      "\tgrad: tensor([-0.0115,  0.0652])\n",
      "\tparams: tensor([  5.3001, -16.9219])\n",
      "Epoch: 2250,Loss: 2.940489\n",
      "\tgrad: tensor([-0.0115,  0.0650])\n",
      "\tparams: tensor([  5.3002, -16.9225])\n",
      "Epoch: 2251,Loss: 2.940446\n",
      "\tgrad: tensor([-0.0115,  0.0649])\n",
      "\tparams: tensor([  5.3003, -16.9232])\n",
      "Epoch: 2252,Loss: 2.940403\n",
      "\tgrad: tensor([-0.0114,  0.0648])\n",
      "\tparams: tensor([  5.3004, -16.9238])\n",
      "Epoch: 2253,Loss: 2.940358\n",
      "\tgrad: tensor([-0.0114,  0.0647])\n",
      "\tparams: tensor([  5.3005, -16.9245])\n",
      "Epoch: 2254,Loss: 2.940316\n",
      "\tgrad: tensor([-0.0114,  0.0646])\n",
      "\tparams: tensor([  5.3006, -16.9251])\n",
      "Epoch: 2255,Loss: 2.940274\n",
      "\tgrad: tensor([-0.0114,  0.0645])\n",
      "\tparams: tensor([  5.3008, -16.9257])\n",
      "Epoch: 2256,Loss: 2.940229\n",
      "\tgrad: tensor([-0.0114,  0.0644])\n",
      "\tparams: tensor([  5.3009, -16.9264])\n",
      "Epoch: 2257,Loss: 2.940188\n",
      "\tgrad: tensor([-0.0114,  0.0643])\n",
      "\tparams: tensor([  5.3010, -16.9270])\n",
      "Epoch: 2258,Loss: 2.940144\n",
      "\tgrad: tensor([-0.0114,  0.0642])\n",
      "\tparams: tensor([  5.3011, -16.9277])\n",
      "Epoch: 2259,Loss: 2.940102\n",
      "\tgrad: tensor([-0.0113,  0.0641])\n",
      "\tparams: tensor([  5.3012, -16.9283])\n",
      "Epoch: 2260,Loss: 2.940060\n",
      "\tgrad: tensor([-0.0113,  0.0640])\n",
      "\tparams: tensor([  5.3013, -16.9290])\n",
      "Epoch: 2261,Loss: 2.940018\n",
      "\tgrad: tensor([-0.0113,  0.0638])\n",
      "\tparams: tensor([  5.3014, -16.9296])\n",
      "Epoch: 2262,Loss: 2.939977\n",
      "\tgrad: tensor([-0.0113,  0.0637])\n",
      "\tparams: tensor([  5.3016, -16.9302])\n",
      "Epoch: 2263,Loss: 2.939934\n",
      "\tgrad: tensor([-0.0112,  0.0636])\n",
      "\tparams: tensor([  5.3017, -16.9309])\n",
      "Epoch: 2264,Loss: 2.939891\n",
      "\tgrad: tensor([-0.0112,  0.0635])\n",
      "\tparams: tensor([  5.3018, -16.9315])\n",
      "Epoch: 2265,Loss: 2.939851\n",
      "\tgrad: tensor([-0.0112,  0.0634])\n",
      "\tparams: tensor([  5.3019, -16.9321])\n",
      "Epoch: 2266,Loss: 2.939809\n",
      "\tgrad: tensor([-0.0112,  0.0633])\n",
      "\tparams: tensor([  5.3020, -16.9328])\n",
      "Epoch: 2267,Loss: 2.939770\n",
      "\tgrad: tensor([-0.0112,  0.0632])\n",
      "\tparams: tensor([  5.3021, -16.9334])\n",
      "Epoch: 2268,Loss: 2.939727\n",
      "\tgrad: tensor([-0.0111,  0.0631])\n",
      "\tparams: tensor([  5.3022, -16.9340])\n",
      "Epoch: 2269,Loss: 2.939686\n",
      "\tgrad: tensor([-0.0111,  0.0630])\n",
      "\tparams: tensor([  5.3023, -16.9347])\n",
      "Epoch: 2270,Loss: 2.939646\n",
      "\tgrad: tensor([-0.0111,  0.0629])\n",
      "\tparams: tensor([  5.3024, -16.9353])\n",
      "Epoch: 2271,Loss: 2.939605\n",
      "\tgrad: tensor([-0.0111,  0.0628])\n",
      "\tparams: tensor([  5.3026, -16.9359])\n",
      "Epoch: 2272,Loss: 2.939566\n",
      "\tgrad: tensor([-0.0111,  0.0627])\n",
      "\tparams: tensor([  5.3027, -16.9365])\n",
      "Epoch: 2273,Loss: 2.939522\n",
      "\tgrad: tensor([-0.0111,  0.0626])\n",
      "\tparams: tensor([  5.3028, -16.9372])\n",
      "Epoch: 2274,Loss: 2.939483\n",
      "\tgrad: tensor([-0.0110,  0.0624])\n",
      "\tparams: tensor([  5.3029, -16.9378])\n",
      "Epoch: 2275,Loss: 2.939443\n",
      "\tgrad: tensor([-0.0110,  0.0623])\n",
      "\tparams: tensor([  5.3030, -16.9384])\n",
      "Epoch: 2276,Loss: 2.939403\n",
      "\tgrad: tensor([-0.0110,  0.0622])\n",
      "\tparams: tensor([  5.3031, -16.9390])\n",
      "Epoch: 2277,Loss: 2.939361\n",
      "\tgrad: tensor([-0.0110,  0.0621])\n",
      "\tparams: tensor([  5.3032, -16.9397])\n",
      "Epoch: 2278,Loss: 2.939323\n",
      "\tgrad: tensor([-0.0110,  0.0620])\n",
      "\tparams: tensor([  5.3033, -16.9403])\n",
      "Epoch: 2279,Loss: 2.939282\n",
      "\tgrad: tensor([-0.0109,  0.0619])\n",
      "\tparams: tensor([  5.3034, -16.9409])\n",
      "Epoch: 2280,Loss: 2.939243\n",
      "\tgrad: tensor([-0.0109,  0.0618])\n",
      "\tparams: tensor([  5.3035, -16.9415])\n",
      "Epoch: 2281,Loss: 2.939205\n",
      "\tgrad: tensor([-0.0109,  0.0617])\n",
      "\tparams: tensor([  5.3037, -16.9421])\n",
      "Epoch: 2282,Loss: 2.939165\n",
      "\tgrad: tensor([-0.0109,  0.0616])\n",
      "\tparams: tensor([  5.3038, -16.9428])\n",
      "Epoch: 2283,Loss: 2.939127\n",
      "\tgrad: tensor([-0.0109,  0.0615])\n",
      "\tparams: tensor([  5.3039, -16.9434])\n",
      "Epoch: 2284,Loss: 2.939087\n",
      "\tgrad: tensor([-0.0108,  0.0614])\n",
      "\tparams: tensor([  5.3040, -16.9440])\n",
      "Epoch: 2285,Loss: 2.939049\n",
      "\tgrad: tensor([-0.0108,  0.0613])\n",
      "\tparams: tensor([  5.3041, -16.9446])\n",
      "Epoch: 2286,Loss: 2.939011\n",
      "\tgrad: tensor([-0.0108,  0.0612])\n",
      "\tparams: tensor([  5.3042, -16.9452])\n",
      "Epoch: 2287,Loss: 2.938971\n",
      "\tgrad: tensor([-0.0108,  0.0611])\n",
      "\tparams: tensor([  5.3043, -16.9458])\n",
      "Epoch: 2288,Loss: 2.938933\n",
      "\tgrad: tensor([-0.0108,  0.0610])\n",
      "\tparams: tensor([  5.3044, -16.9464])\n",
      "Epoch: 2289,Loss: 2.938893\n",
      "\tgrad: tensor([-0.0108,  0.0609])\n",
      "\tparams: tensor([  5.3045, -16.9470])\n",
      "Epoch: 2290,Loss: 2.938857\n",
      "\tgrad: tensor([-0.0107,  0.0608])\n",
      "\tparams: tensor([  5.3046, -16.9476])\n",
      "Epoch: 2291,Loss: 2.938820\n",
      "\tgrad: tensor([-0.0107,  0.0607])\n",
      "\tparams: tensor([  5.3047, -16.9482])\n",
      "Epoch: 2292,Loss: 2.938779\n",
      "\tgrad: tensor([-0.0107,  0.0606])\n",
      "\tparams: tensor([  5.3048, -16.9489])\n",
      "Epoch: 2293,Loss: 2.938743\n",
      "\tgrad: tensor([-0.0107,  0.0605])\n",
      "\tparams: tensor([  5.3049, -16.9495])\n",
      "Epoch: 2294,Loss: 2.938705\n",
      "\tgrad: tensor([-0.0107,  0.0604])\n",
      "\tparams: tensor([  5.3051, -16.9501])\n",
      "Epoch: 2295,Loss: 2.938667\n",
      "\tgrad: tensor([-0.0106,  0.0603])\n",
      "\tparams: tensor([  5.3052, -16.9507])\n",
      "Epoch: 2296,Loss: 2.938629\n",
      "\tgrad: tensor([-0.0106,  0.0602])\n",
      "\tparams: tensor([  5.3053, -16.9513])\n",
      "Epoch: 2297,Loss: 2.938593\n",
      "\tgrad: tensor([-0.0106,  0.0601])\n",
      "\tparams: tensor([  5.3054, -16.9519])\n",
      "Epoch: 2298,Loss: 2.938555\n",
      "\tgrad: tensor([-0.0106,  0.0600])\n",
      "\tparams: tensor([  5.3055, -16.9525])\n",
      "Epoch: 2299,Loss: 2.938519\n",
      "\tgrad: tensor([-0.0106,  0.0598])\n",
      "\tparams: tensor([  5.3056, -16.9531])\n",
      "Epoch: 2300,Loss: 2.938481\n",
      "\tgrad: tensor([-0.0106,  0.0597])\n",
      "\tparams: tensor([  5.3057, -16.9537])\n",
      "Epoch: 2301,Loss: 2.938444\n",
      "\tgrad: tensor([-0.0105,  0.0596])\n",
      "\tparams: tensor([  5.3058, -16.9543])\n",
      "Epoch: 2302,Loss: 2.938408\n",
      "\tgrad: tensor([-0.0105,  0.0595])\n",
      "\tparams: tensor([  5.3059, -16.9549])\n",
      "Epoch: 2303,Loss: 2.938371\n",
      "\tgrad: tensor([-0.0105,  0.0594])\n",
      "\tparams: tensor([  5.3060, -16.9554])\n",
      "Epoch: 2304,Loss: 2.938335\n",
      "\tgrad: tensor([-0.0105,  0.0593])\n",
      "\tparams: tensor([  5.3061, -16.9560])\n",
      "Epoch: 2305,Loss: 2.938299\n",
      "\tgrad: tensor([-0.0105,  0.0592])\n",
      "\tparams: tensor([  5.3062, -16.9566])\n",
      "Epoch: 2306,Loss: 2.938263\n",
      "\tgrad: tensor([-0.0105,  0.0591])\n",
      "\tparams: tensor([  5.3063, -16.9572])\n",
      "Epoch: 2307,Loss: 2.938227\n",
      "\tgrad: tensor([-0.0104,  0.0590])\n",
      "\tparams: tensor([  5.3064, -16.9578])\n",
      "Epoch: 2308,Loss: 2.938190\n",
      "\tgrad: tensor([-0.0104,  0.0589])\n",
      "\tparams: tensor([  5.3065, -16.9584])\n",
      "Epoch: 2309,Loss: 2.938155\n",
      "\tgrad: tensor([-0.0104,  0.0588])\n",
      "\tparams: tensor([  5.3066, -16.9590])\n",
      "Epoch: 2310,Loss: 2.938118\n",
      "\tgrad: tensor([-0.0104,  0.0587])\n",
      "\tparams: tensor([  5.3067, -16.9596])\n",
      "Epoch: 2311,Loss: 2.938084\n",
      "\tgrad: tensor([-0.0104,  0.0586])\n",
      "\tparams: tensor([  5.3068, -16.9602])\n",
      "Epoch: 2312,Loss: 2.938049\n",
      "\tgrad: tensor([-0.0103,  0.0585])\n",
      "\tparams: tensor([  5.3069, -16.9608])\n",
      "Epoch: 2313,Loss: 2.938014\n",
      "\tgrad: tensor([-0.0103,  0.0584])\n",
      "\tparams: tensor([  5.3070, -16.9613])\n",
      "Epoch: 2314,Loss: 2.937977\n",
      "\tgrad: tensor([-0.0103,  0.0583])\n",
      "\tparams: tensor([  5.3072, -16.9619])\n",
      "Epoch: 2315,Loss: 2.937943\n",
      "\tgrad: tensor([-0.0103,  0.0582])\n",
      "\tparams: tensor([  5.3073, -16.9625])\n",
      "Epoch: 2316,Loss: 2.937908\n",
      "\tgrad: tensor([-0.0103,  0.0581])\n",
      "\tparams: tensor([  5.3074, -16.9631])\n",
      "Epoch: 2317,Loss: 2.937872\n",
      "\tgrad: tensor([-0.0103,  0.0580])\n",
      "\tparams: tensor([  5.3075, -16.9637])\n",
      "Epoch: 2318,Loss: 2.937839\n",
      "\tgrad: tensor([-0.0102,  0.0580])\n",
      "\tparams: tensor([  5.3076, -16.9642])\n",
      "Epoch: 2319,Loss: 2.937804\n",
      "\tgrad: tensor([-0.0102,  0.0578])\n",
      "\tparams: tensor([  5.3077, -16.9648])\n",
      "Epoch: 2320,Loss: 2.937769\n",
      "\tgrad: tensor([-0.0102,  0.0578])\n",
      "\tparams: tensor([  5.3078, -16.9654])\n",
      "Epoch: 2321,Loss: 2.937734\n",
      "\tgrad: tensor([-0.0102,  0.0577])\n",
      "\tparams: tensor([  5.3079, -16.9660])\n",
      "Epoch: 2322,Loss: 2.937700\n",
      "\tgrad: tensor([-0.0102,  0.0576])\n",
      "\tparams: tensor([  5.3080, -16.9666])\n",
      "Epoch: 2323,Loss: 2.937665\n",
      "\tgrad: tensor([-0.0102,  0.0575])\n",
      "\tparams: tensor([  5.3081, -16.9671])\n",
      "Epoch: 2324,Loss: 2.937632\n",
      "\tgrad: tensor([-0.0101,  0.0574])\n",
      "\tparams: tensor([  5.3082, -16.9677])\n",
      "Epoch: 2325,Loss: 2.937598\n",
      "\tgrad: tensor([-0.0101,  0.0573])\n",
      "\tparams: tensor([  5.3083, -16.9683])\n",
      "Epoch: 2326,Loss: 2.937565\n",
      "\tgrad: tensor([-0.0101,  0.0572])\n",
      "\tparams: tensor([  5.3084, -16.9688])\n",
      "Epoch: 2327,Loss: 2.937531\n",
      "\tgrad: tensor([-0.0101,  0.0571])\n",
      "\tparams: tensor([  5.3085, -16.9694])\n",
      "Epoch: 2328,Loss: 2.937499\n",
      "\tgrad: tensor([-0.0101,  0.0570])\n",
      "\tparams: tensor([  5.3086, -16.9700])\n",
      "Epoch: 2329,Loss: 2.937465\n",
      "\tgrad: tensor([-0.0101,  0.0569])\n",
      "\tparams: tensor([  5.3087, -16.9706])\n",
      "Epoch: 2330,Loss: 2.937430\n",
      "\tgrad: tensor([-0.0100,  0.0568])\n",
      "\tparams: tensor([  5.3088, -16.9711])\n",
      "Epoch: 2331,Loss: 2.937398\n",
      "\tgrad: tensor([-0.0100,  0.0567])\n",
      "\tparams: tensor([  5.3089, -16.9717])\n",
      "Epoch: 2332,Loss: 2.937364\n",
      "\tgrad: tensor([-0.0100,  0.0566])\n",
      "\tparams: tensor([  5.3090, -16.9723])\n",
      "Epoch: 2333,Loss: 2.937332\n",
      "\tgrad: tensor([-0.0100,  0.0565])\n",
      "\tparams: tensor([  5.3091, -16.9728])\n",
      "Epoch: 2334,Loss: 2.937299\n",
      "\tgrad: tensor([-0.0100,  0.0564])\n",
      "\tparams: tensor([  5.3092, -16.9734])\n",
      "Epoch: 2335,Loss: 2.937265\n",
      "\tgrad: tensor([-0.0100,  0.0563])\n",
      "\tparams: tensor([  5.3093, -16.9739])\n",
      "Epoch: 2336,Loss: 2.937232\n",
      "\tgrad: tensor([-0.0099,  0.0562])\n",
      "\tparams: tensor([  5.3094, -16.9745])\n",
      "Epoch: 2337,Loss: 2.937201\n",
      "\tgrad: tensor([-0.0099,  0.0561])\n",
      "\tparams: tensor([  5.3095, -16.9751])\n",
      "Epoch: 2338,Loss: 2.937167\n",
      "\tgrad: tensor([-0.0099,  0.0560])\n",
      "\tparams: tensor([  5.3096, -16.9756])\n",
      "Epoch: 2339,Loss: 2.937134\n",
      "\tgrad: tensor([-0.0099,  0.0559])\n",
      "\tparams: tensor([  5.3097, -16.9762])\n",
      "Epoch: 2340,Loss: 2.937104\n",
      "\tgrad: tensor([-0.0099,  0.0558])\n",
      "\tparams: tensor([  5.3098, -16.9767])\n",
      "Epoch: 2341,Loss: 2.937071\n",
      "\tgrad: tensor([-0.0098,  0.0557])\n",
      "\tparams: tensor([  5.3099, -16.9773])\n",
      "Epoch: 2342,Loss: 2.937039\n",
      "\tgrad: tensor([-0.0098,  0.0556])\n",
      "\tparams: tensor([  5.3100, -16.9779])\n",
      "Epoch: 2343,Loss: 2.937008\n",
      "\tgrad: tensor([-0.0098,  0.0555])\n",
      "\tparams: tensor([  5.3101, -16.9784])\n",
      "Epoch: 2344,Loss: 2.936976\n",
      "\tgrad: tensor([-0.0098,  0.0554])\n",
      "\tparams: tensor([  5.3102, -16.9790])\n",
      "Epoch: 2345,Loss: 2.936945\n",
      "\tgrad: tensor([-0.0098,  0.0553])\n",
      "\tparams: tensor([  5.3103, -16.9795])\n",
      "Epoch: 2346,Loss: 2.936912\n",
      "\tgrad: tensor([-0.0098,  0.0553])\n",
      "\tparams: tensor([  5.3104, -16.9801])\n",
      "Epoch: 2347,Loss: 2.936883\n",
      "\tgrad: tensor([-0.0097,  0.0552])\n",
      "\tparams: tensor([  5.3105, -16.9806])\n",
      "Epoch: 2348,Loss: 2.936851\n",
      "\tgrad: tensor([-0.0097,  0.0551])\n",
      "\tparams: tensor([  5.3106, -16.9812])\n",
      "Epoch: 2349,Loss: 2.936819\n",
      "\tgrad: tensor([-0.0097,  0.0550])\n",
      "\tparams: tensor([  5.3107, -16.9817])\n",
      "Epoch: 2350,Loss: 2.936788\n",
      "\tgrad: tensor([-0.0097,  0.0549])\n",
      "\tparams: tensor([  5.3107, -16.9823])\n",
      "Epoch: 2351,Loss: 2.936757\n",
      "\tgrad: tensor([-0.0097,  0.0548])\n",
      "\tparams: tensor([  5.3108, -16.9828])\n",
      "Epoch: 2352,Loss: 2.936725\n",
      "\tgrad: tensor([-0.0097,  0.0547])\n",
      "\tparams: tensor([  5.3109, -16.9834])\n",
      "Epoch: 2353,Loss: 2.936694\n",
      "\tgrad: tensor([-0.0096,  0.0546])\n",
      "\tparams: tensor([  5.3110, -16.9839])\n",
      "Epoch: 2354,Loss: 2.936665\n",
      "\tgrad: tensor([-0.0096,  0.0545])\n",
      "\tparams: tensor([  5.3111, -16.9845])\n",
      "Epoch: 2355,Loss: 2.936633\n",
      "\tgrad: tensor([-0.0096,  0.0544])\n",
      "\tparams: tensor([  5.3112, -16.9850])\n",
      "Epoch: 2356,Loss: 2.936602\n",
      "\tgrad: tensor([-0.0096,  0.0543])\n",
      "\tparams: tensor([  5.3113, -16.9856])\n",
      "Epoch: 2357,Loss: 2.936572\n",
      "\tgrad: tensor([-0.0096,  0.0542])\n",
      "\tparams: tensor([  5.3114, -16.9861])\n",
      "Epoch: 2358,Loss: 2.936542\n",
      "\tgrad: tensor([-0.0095,  0.0541])\n",
      "\tparams: tensor([  5.3115, -16.9866])\n",
      "Epoch: 2359,Loss: 2.936511\n",
      "\tgrad: tensor([-0.0096,  0.0540])\n",
      "\tparams: tensor([  5.3116, -16.9872])\n",
      "Epoch: 2360,Loss: 2.936481\n",
      "\tgrad: tensor([-0.0095,  0.0540])\n",
      "\tparams: tensor([  5.3117, -16.9877])\n",
      "Epoch: 2361,Loss: 2.936451\n",
      "\tgrad: tensor([-0.0095,  0.0539])\n",
      "\tparams: tensor([  5.3118, -16.9883])\n",
      "Epoch: 2362,Loss: 2.936421\n",
      "\tgrad: tensor([-0.0095,  0.0538])\n",
      "\tparams: tensor([  5.3119, -16.9888])\n",
      "Epoch: 2363,Loss: 2.936392\n",
      "\tgrad: tensor([-0.0095,  0.0537])\n",
      "\tparams: tensor([  5.3120, -16.9893])\n",
      "Epoch: 2364,Loss: 2.936362\n",
      "\tgrad: tensor([-0.0094,  0.0536])\n",
      "\tparams: tensor([  5.3121, -16.9899])\n",
      "Epoch: 2365,Loss: 2.936332\n",
      "\tgrad: tensor([-0.0094,  0.0535])\n",
      "\tparams: tensor([  5.3122, -16.9904])\n",
      "Epoch: 2366,Loss: 2.936304\n",
      "\tgrad: tensor([-0.0094,  0.0534])\n",
      "\tparams: tensor([  5.3123, -16.9909])\n",
      "Epoch: 2367,Loss: 2.936274\n",
      "\tgrad: tensor([-0.0094,  0.0533])\n",
      "\tparams: tensor([  5.3124, -16.9915])\n",
      "Epoch: 2368,Loss: 2.936244\n",
      "\tgrad: tensor([-0.0094,  0.0532])\n",
      "\tparams: tensor([  5.3125, -16.9920])\n",
      "Epoch: 2369,Loss: 2.936216\n",
      "\tgrad: tensor([-0.0094,  0.0531])\n",
      "\tparams: tensor([  5.3126, -16.9925])\n",
      "Epoch: 2370,Loss: 2.936188\n",
      "\tgrad: tensor([-0.0094,  0.0530])\n",
      "\tparams: tensor([  5.3127, -16.9931])\n",
      "Epoch: 2371,Loss: 2.936156\n",
      "\tgrad: tensor([-0.0094,  0.0530])\n",
      "\tparams: tensor([  5.3127, -16.9936])\n",
      "Epoch: 2372,Loss: 2.936128\n",
      "\tgrad: tensor([-0.0093,  0.0529])\n",
      "\tparams: tensor([  5.3128, -16.9941])\n",
      "Epoch: 2373,Loss: 2.936100\n",
      "\tgrad: tensor([-0.0093,  0.0528])\n",
      "\tparams: tensor([  5.3129, -16.9946])\n",
      "Epoch: 2374,Loss: 2.936072\n",
      "\tgrad: tensor([-0.0093,  0.0527])\n",
      "\tparams: tensor([  5.3130, -16.9952])\n",
      "Epoch: 2375,Loss: 2.936042\n",
      "\tgrad: tensor([-0.0093,  0.0526])\n",
      "\tparams: tensor([  5.3131, -16.9957])\n",
      "Epoch: 2376,Loss: 2.936014\n",
      "\tgrad: tensor([-0.0093,  0.0525])\n",
      "\tparams: tensor([  5.3132, -16.9962])\n",
      "Epoch: 2377,Loss: 2.935986\n",
      "\tgrad: tensor([-0.0093,  0.0524])\n",
      "\tparams: tensor([  5.3133, -16.9967])\n",
      "Epoch: 2378,Loss: 2.935957\n",
      "\tgrad: tensor([-0.0093,  0.0523])\n",
      "\tparams: tensor([  5.3134, -16.9973])\n",
      "Epoch: 2379,Loss: 2.935928\n",
      "\tgrad: tensor([-0.0092,  0.0522])\n",
      "\tparams: tensor([  5.3135, -16.9978])\n",
      "Epoch: 2380,Loss: 2.935901\n",
      "\tgrad: tensor([-0.0092,  0.0522])\n",
      "\tparams: tensor([  5.3136, -16.9983])\n",
      "Epoch: 2381,Loss: 2.935873\n",
      "\tgrad: tensor([-0.0092,  0.0521])\n",
      "\tparams: tensor([  5.3137, -16.9988])\n",
      "Epoch: 2382,Loss: 2.935845\n",
      "\tgrad: tensor([-0.0092,  0.0520])\n",
      "\tparams: tensor([  5.3138, -16.9994])\n",
      "Epoch: 2383,Loss: 2.935817\n",
      "\tgrad: tensor([-0.0092,  0.0519])\n",
      "\tparams: tensor([  5.3139, -16.9999])\n",
      "Epoch: 2384,Loss: 2.935789\n",
      "\tgrad: tensor([-0.0092,  0.0518])\n",
      "\tparams: tensor([  5.3139, -17.0004])\n",
      "Epoch: 2385,Loss: 2.935762\n",
      "\tgrad: tensor([-0.0092,  0.0517])\n",
      "\tparams: tensor([  5.3140, -17.0009])\n",
      "Epoch: 2386,Loss: 2.935734\n",
      "\tgrad: tensor([-0.0091,  0.0516])\n",
      "\tparams: tensor([  5.3141, -17.0014])\n",
      "Epoch: 2387,Loss: 2.935707\n",
      "\tgrad: tensor([-0.0091,  0.0515])\n",
      "\tparams: tensor([  5.3142, -17.0019])\n",
      "Epoch: 2388,Loss: 2.935679\n",
      "\tgrad: tensor([-0.0091,  0.0514])\n",
      "\tparams: tensor([  5.3143, -17.0025])\n",
      "Epoch: 2389,Loss: 2.935650\n",
      "\tgrad: tensor([-0.0091,  0.0514])\n",
      "\tparams: tensor([  5.3144, -17.0030])\n",
      "Epoch: 2390,Loss: 2.935626\n",
      "\tgrad: tensor([-0.0090,  0.0513])\n",
      "\tparams: tensor([  5.3145, -17.0035])\n",
      "Epoch: 2391,Loss: 2.935596\n",
      "\tgrad: tensor([-0.0090,  0.0512])\n",
      "\tparams: tensor([  5.3146, -17.0040])\n",
      "Epoch: 2392,Loss: 2.935571\n",
      "\tgrad: tensor([-0.0090,  0.0511])\n",
      "\tparams: tensor([  5.3147, -17.0045])\n",
      "Epoch: 2393,Loss: 2.935544\n",
      "\tgrad: tensor([-0.0090,  0.0510])\n",
      "\tparams: tensor([  5.3148, -17.0050])\n",
      "Epoch: 2394,Loss: 2.935516\n",
      "\tgrad: tensor([-0.0090,  0.0509])\n",
      "\tparams: tensor([  5.3149, -17.0055])\n",
      "Epoch: 2395,Loss: 2.935489\n",
      "\tgrad: tensor([-0.0090,  0.0508])\n",
      "\tparams: tensor([  5.3149, -17.0060])\n",
      "Epoch: 2396,Loss: 2.935465\n",
      "\tgrad: tensor([-0.0090,  0.0507])\n",
      "\tparams: tensor([  5.3150, -17.0065])\n",
      "Epoch: 2397,Loss: 2.935436\n",
      "\tgrad: tensor([-0.0090,  0.0507])\n",
      "\tparams: tensor([  5.3151, -17.0070])\n",
      "Epoch: 2398,Loss: 2.935411\n",
      "\tgrad: tensor([-0.0089,  0.0506])\n",
      "\tparams: tensor([  5.3152, -17.0076])\n",
      "Epoch: 2399,Loss: 2.935385\n",
      "\tgrad: tensor([-0.0089,  0.0505])\n",
      "\tparams: tensor([  5.3153, -17.0081])\n",
      "Epoch: 2400,Loss: 2.935356\n",
      "\tgrad: tensor([-0.0089,  0.0504])\n",
      "\tparams: tensor([  5.3154, -17.0086])\n",
      "Epoch: 2401,Loss: 2.935332\n",
      "\tgrad: tensor([-0.0089,  0.0503])\n",
      "\tparams: tensor([  5.3155, -17.0091])\n",
      "Epoch: 2402,Loss: 2.935304\n",
      "\tgrad: tensor([-0.0089,  0.0502])\n",
      "\tparams: tensor([  5.3156, -17.0096])\n",
      "Epoch: 2403,Loss: 2.935281\n",
      "\tgrad: tensor([-0.0088,  0.0502])\n",
      "\tparams: tensor([  5.3157, -17.0101])\n",
      "Epoch: 2404,Loss: 2.935252\n",
      "\tgrad: tensor([-0.0088,  0.0501])\n",
      "\tparams: tensor([  5.3157, -17.0106])\n",
      "Epoch: 2405,Loss: 2.935228\n",
      "\tgrad: tensor([-0.0088,  0.0500])\n",
      "\tparams: tensor([  5.3158, -17.0111])\n",
      "Epoch: 2406,Loss: 2.935203\n",
      "\tgrad: tensor([-0.0088,  0.0499])\n",
      "\tparams: tensor([  5.3159, -17.0116])\n",
      "Epoch: 2407,Loss: 2.935177\n",
      "\tgrad: tensor([-0.0088,  0.0498])\n",
      "\tparams: tensor([  5.3160, -17.0121])\n",
      "Epoch: 2408,Loss: 2.935152\n",
      "\tgrad: tensor([-0.0088,  0.0497])\n",
      "\tparams: tensor([  5.3161, -17.0126])\n",
      "Epoch: 2409,Loss: 2.935126\n",
      "\tgrad: tensor([-0.0088,  0.0496])\n",
      "\tparams: tensor([  5.3162, -17.0131])\n",
      "Epoch: 2410,Loss: 2.935100\n",
      "\tgrad: tensor([-0.0088,  0.0496])\n",
      "\tparams: tensor([  5.3163, -17.0136])\n",
      "Epoch: 2411,Loss: 2.935075\n",
      "\tgrad: tensor([-0.0087,  0.0495])\n",
      "\tparams: tensor([  5.3164, -17.0140])\n",
      "Epoch: 2412,Loss: 2.935049\n",
      "\tgrad: tensor([-0.0087,  0.0494])\n",
      "\tparams: tensor([  5.3164, -17.0145])\n",
      "Epoch: 2413,Loss: 2.935024\n",
      "\tgrad: tensor([-0.0087,  0.0493])\n",
      "\tparams: tensor([  5.3165, -17.0150])\n",
      "Epoch: 2414,Loss: 2.935001\n",
      "\tgrad: tensor([-0.0087,  0.0492])\n",
      "\tparams: tensor([  5.3166, -17.0155])\n",
      "Epoch: 2415,Loss: 2.934973\n",
      "\tgrad: tensor([-0.0087,  0.0491])\n",
      "\tparams: tensor([  5.3167, -17.0160])\n",
      "Epoch: 2416,Loss: 2.934949\n",
      "\tgrad: tensor([-0.0087,  0.0491])\n",
      "\tparams: tensor([  5.3168, -17.0165])\n",
      "Epoch: 2417,Loss: 2.934925\n",
      "\tgrad: tensor([-0.0086,  0.0490])\n",
      "\tparams: tensor([  5.3169, -17.0170])\n",
      "Epoch: 2418,Loss: 2.934899\n",
      "\tgrad: tensor([-0.0086,  0.0489])\n",
      "\tparams: tensor([  5.3170, -17.0175])\n",
      "Epoch: 2419,Loss: 2.934876\n",
      "\tgrad: tensor([-0.0086,  0.0488])\n",
      "\tparams: tensor([  5.3171, -17.0180])\n",
      "Epoch: 2420,Loss: 2.934853\n",
      "\tgrad: tensor([-0.0086,  0.0487])\n",
      "\tparams: tensor([  5.3171, -17.0185])\n",
      "Epoch: 2421,Loss: 2.934826\n",
      "\tgrad: tensor([-0.0086,  0.0486])\n",
      "\tparams: tensor([  5.3172, -17.0189])\n",
      "Epoch: 2422,Loss: 2.934802\n",
      "\tgrad: tensor([-0.0086,  0.0486])\n",
      "\tparams: tensor([  5.3173, -17.0194])\n",
      "Epoch: 2423,Loss: 2.934777\n",
      "\tgrad: tensor([-0.0086,  0.0485])\n",
      "\tparams: tensor([  5.3174, -17.0199])\n",
      "Epoch: 2424,Loss: 2.934753\n",
      "\tgrad: tensor([-0.0086,  0.0484])\n",
      "\tparams: tensor([  5.3175, -17.0204])\n",
      "Epoch: 2425,Loss: 2.934730\n",
      "\tgrad: tensor([-0.0086,  0.0483])\n",
      "\tparams: tensor([  5.3176, -17.0209])\n",
      "Epoch: 2426,Loss: 2.934705\n",
      "\tgrad: tensor([-0.0085,  0.0482])\n",
      "\tparams: tensor([  5.3177, -17.0214])\n",
      "Epoch: 2427,Loss: 2.934681\n",
      "\tgrad: tensor([-0.0085,  0.0481])\n",
      "\tparams: tensor([  5.3177, -17.0219])\n",
      "Epoch: 2428,Loss: 2.934658\n",
      "\tgrad: tensor([-0.0085,  0.0481])\n",
      "\tparams: tensor([  5.3178, -17.0223])\n",
      "Epoch: 2429,Loss: 2.934635\n",
      "\tgrad: tensor([-0.0085,  0.0480])\n",
      "\tparams: tensor([  5.3179, -17.0228])\n",
      "Epoch: 2430,Loss: 2.934609\n",
      "\tgrad: tensor([-0.0085,  0.0479])\n",
      "\tparams: tensor([  5.3180, -17.0233])\n",
      "Epoch: 2431,Loss: 2.934585\n",
      "\tgrad: tensor([-0.0084,  0.0478])\n",
      "\tparams: tensor([  5.3181, -17.0238])\n",
      "Epoch: 2432,Loss: 2.934563\n",
      "\tgrad: tensor([-0.0084,  0.0477])\n",
      "\tparams: tensor([  5.3182, -17.0242])\n",
      "Epoch: 2433,Loss: 2.934541\n",
      "\tgrad: tensor([-0.0084,  0.0477])\n",
      "\tparams: tensor([  5.3182, -17.0247])\n",
      "Epoch: 2434,Loss: 2.934516\n",
      "\tgrad: tensor([-0.0084,  0.0476])\n",
      "\tparams: tensor([  5.3183, -17.0252])\n",
      "Epoch: 2435,Loss: 2.934493\n",
      "\tgrad: tensor([-0.0084,  0.0475])\n",
      "\tparams: tensor([  5.3184, -17.0257])\n",
      "Epoch: 2436,Loss: 2.934469\n",
      "\tgrad: tensor([-0.0084,  0.0474])\n",
      "\tparams: tensor([  5.3185, -17.0261])\n",
      "Epoch: 2437,Loss: 2.934446\n",
      "\tgrad: tensor([-0.0084,  0.0473])\n",
      "\tparams: tensor([  5.3186, -17.0266])\n",
      "Epoch: 2438,Loss: 2.934423\n",
      "\tgrad: tensor([-0.0083,  0.0473])\n",
      "\tparams: tensor([  5.3187, -17.0271])\n",
      "Epoch: 2439,Loss: 2.934400\n",
      "\tgrad: tensor([-0.0083,  0.0472])\n",
      "\tparams: tensor([  5.3187, -17.0276])\n",
      "Epoch: 2440,Loss: 2.934377\n",
      "\tgrad: tensor([-0.0083,  0.0471])\n",
      "\tparams: tensor([  5.3188, -17.0280])\n",
      "Epoch: 2441,Loss: 2.934355\n",
      "\tgrad: tensor([-0.0083,  0.0470])\n",
      "\tparams: tensor([  5.3189, -17.0285])\n",
      "Epoch: 2442,Loss: 2.934331\n",
      "\tgrad: tensor([-0.0083,  0.0469])\n",
      "\tparams: tensor([  5.3190, -17.0290])\n",
      "Epoch: 2443,Loss: 2.934309\n",
      "\tgrad: tensor([-0.0083,  0.0469])\n",
      "\tparams: tensor([  5.3191, -17.0294])\n",
      "Epoch: 2444,Loss: 2.934287\n",
      "\tgrad: tensor([-0.0083,  0.0468])\n",
      "\tparams: tensor([  5.3192, -17.0299])\n",
      "Epoch: 2445,Loss: 2.934264\n",
      "\tgrad: tensor([-0.0083,  0.0467])\n",
      "\tparams: tensor([  5.3192, -17.0304])\n",
      "Epoch: 2446,Loss: 2.934242\n",
      "\tgrad: tensor([-0.0083,  0.0466])\n",
      "\tparams: tensor([  5.3193, -17.0308])\n",
      "Epoch: 2447,Loss: 2.934219\n",
      "\tgrad: tensor([-0.0082,  0.0465])\n",
      "\tparams: tensor([  5.3194, -17.0313])\n",
      "Epoch: 2448,Loss: 2.934198\n",
      "\tgrad: tensor([-0.0082,  0.0465])\n",
      "\tparams: tensor([  5.3195, -17.0318])\n",
      "Epoch: 2449,Loss: 2.934175\n",
      "\tgrad: tensor([-0.0082,  0.0464])\n",
      "\tparams: tensor([  5.3196, -17.0322])\n",
      "Epoch: 2450,Loss: 2.934151\n",
      "\tgrad: tensor([-0.0082,  0.0463])\n",
      "\tparams: tensor([  5.3197, -17.0327])\n",
      "Epoch: 2451,Loss: 2.934129\n",
      "\tgrad: tensor([-0.0082,  0.0462])\n",
      "\tparams: tensor([  5.3197, -17.0332])\n",
      "Epoch: 2452,Loss: 2.934108\n",
      "\tgrad: tensor([-0.0082,  0.0461])\n",
      "\tparams: tensor([  5.3198, -17.0336])\n",
      "Epoch: 2453,Loss: 2.934084\n",
      "\tgrad: tensor([-0.0081,  0.0461])\n",
      "\tparams: tensor([  5.3199, -17.0341])\n",
      "Epoch: 2454,Loss: 2.934065\n",
      "\tgrad: tensor([-0.0081,  0.0460])\n",
      "\tparams: tensor([  5.3200, -17.0345])\n",
      "Epoch: 2455,Loss: 2.934043\n",
      "\tgrad: tensor([-0.0081,  0.0459])\n",
      "\tparams: tensor([  5.3201, -17.0350])\n",
      "Epoch: 2456,Loss: 2.934020\n",
      "\tgrad: tensor([-0.0081,  0.0458])\n",
      "\tparams: tensor([  5.3201, -17.0355])\n",
      "Epoch: 2457,Loss: 2.934000\n",
      "\tgrad: tensor([-0.0081,  0.0457])\n",
      "\tparams: tensor([  5.3202, -17.0359])\n",
      "Epoch: 2458,Loss: 2.933978\n",
      "\tgrad: tensor([-0.0081,  0.0457])\n",
      "\tparams: tensor([  5.3203, -17.0364])\n",
      "Epoch: 2459,Loss: 2.933956\n",
      "\tgrad: tensor([-0.0080,  0.0456])\n",
      "\tparams: tensor([  5.3204, -17.0368])\n",
      "Epoch: 2460,Loss: 2.933935\n",
      "\tgrad: tensor([-0.0080,  0.0455])\n",
      "\tparams: tensor([  5.3205, -17.0373])\n",
      "Epoch: 2461,Loss: 2.933914\n",
      "\tgrad: tensor([-0.0080,  0.0454])\n",
      "\tparams: tensor([  5.3205, -17.0377])\n",
      "Epoch: 2462,Loss: 2.933893\n",
      "\tgrad: tensor([-0.0080,  0.0454])\n",
      "\tparams: tensor([  5.3206, -17.0382])\n",
      "Epoch: 2463,Loss: 2.933871\n",
      "\tgrad: tensor([-0.0080,  0.0453])\n",
      "\tparams: tensor([  5.3207, -17.0386])\n",
      "Epoch: 2464,Loss: 2.933849\n",
      "\tgrad: tensor([-0.0080,  0.0452])\n",
      "\tparams: tensor([  5.3208, -17.0391])\n",
      "Epoch: 2465,Loss: 2.933828\n",
      "\tgrad: tensor([-0.0080,  0.0451])\n",
      "\tparams: tensor([  5.3209, -17.0396])\n",
      "Epoch: 2466,Loss: 2.933807\n",
      "\tgrad: tensor([-0.0080,  0.0451])\n",
      "\tparams: tensor([  5.3209, -17.0400])\n",
      "Epoch: 2467,Loss: 2.933787\n",
      "\tgrad: tensor([-0.0079,  0.0450])\n",
      "\tparams: tensor([  5.3210, -17.0405])\n",
      "Epoch: 2468,Loss: 2.933767\n",
      "\tgrad: tensor([-0.0079,  0.0449])\n",
      "\tparams: tensor([  5.3211, -17.0409])\n",
      "Epoch: 2469,Loss: 2.933746\n",
      "\tgrad: tensor([-0.0079,  0.0448])\n",
      "\tparams: tensor([  5.3212, -17.0413])\n",
      "Epoch: 2470,Loss: 2.933723\n",
      "\tgrad: tensor([-0.0079,  0.0448])\n",
      "\tparams: tensor([  5.3213, -17.0418])\n",
      "Epoch: 2471,Loss: 2.933704\n",
      "\tgrad: tensor([-0.0079,  0.0447])\n",
      "\tparams: tensor([  5.3213, -17.0422])\n",
      "Epoch: 2472,Loss: 2.933682\n",
      "\tgrad: tensor([-0.0079,  0.0446])\n",
      "\tparams: tensor([  5.3214, -17.0427])\n",
      "Epoch: 2473,Loss: 2.933662\n",
      "\tgrad: tensor([-0.0079,  0.0445])\n",
      "\tparams: tensor([  5.3215, -17.0431])\n",
      "Epoch: 2474,Loss: 2.933643\n",
      "\tgrad: tensor([-0.0079,  0.0444])\n",
      "\tparams: tensor([  5.3216, -17.0436])\n",
      "Epoch: 2475,Loss: 2.933622\n",
      "\tgrad: tensor([-0.0078,  0.0444])\n",
      "\tparams: tensor([  5.3217, -17.0440])\n",
      "Epoch: 2476,Loss: 2.933602\n",
      "\tgrad: tensor([-0.0078,  0.0443])\n",
      "\tparams: tensor([  5.3217, -17.0445])\n",
      "Epoch: 2477,Loss: 2.933583\n",
      "\tgrad: tensor([-0.0078,  0.0442])\n",
      "\tparams: tensor([  5.3218, -17.0449])\n",
      "Epoch: 2478,Loss: 2.933561\n",
      "\tgrad: tensor([-0.0078,  0.0441])\n",
      "\tparams: tensor([  5.3219, -17.0453])\n",
      "Epoch: 2479,Loss: 2.933541\n",
      "\tgrad: tensor([-0.0078,  0.0441])\n",
      "\tparams: tensor([  5.3220, -17.0458])\n",
      "Epoch: 2480,Loss: 2.933521\n",
      "\tgrad: tensor([-0.0078,  0.0440])\n",
      "\tparams: tensor([  5.3220, -17.0462])\n",
      "Epoch: 2481,Loss: 2.933501\n",
      "\tgrad: tensor([-0.0078,  0.0439])\n",
      "\tparams: tensor([  5.3221, -17.0467])\n",
      "Epoch: 2482,Loss: 2.933480\n",
      "\tgrad: tensor([-0.0077,  0.0438])\n",
      "\tparams: tensor([  5.3222, -17.0471])\n",
      "Epoch: 2483,Loss: 2.933463\n",
      "\tgrad: tensor([-0.0077,  0.0438])\n",
      "\tparams: tensor([  5.3223, -17.0475])\n",
      "Epoch: 2484,Loss: 2.933442\n",
      "\tgrad: tensor([-0.0077,  0.0437])\n",
      "\tparams: tensor([  5.3224, -17.0480])\n",
      "Epoch: 2485,Loss: 2.933422\n",
      "\tgrad: tensor([-0.0077,  0.0436])\n",
      "\tparams: tensor([  5.3224, -17.0484])\n",
      "Epoch: 2486,Loss: 2.933403\n",
      "\tgrad: tensor([-0.0077,  0.0436])\n",
      "\tparams: tensor([  5.3225, -17.0489])\n",
      "Epoch: 2487,Loss: 2.933382\n",
      "\tgrad: tensor([-0.0077,  0.0435])\n",
      "\tparams: tensor([  5.3226, -17.0493])\n",
      "Epoch: 2488,Loss: 2.933365\n",
      "\tgrad: tensor([-0.0077,  0.0434])\n",
      "\tparams: tensor([  5.3227, -17.0497])\n",
      "Epoch: 2489,Loss: 2.933345\n",
      "\tgrad: tensor([-0.0077,  0.0433])\n",
      "\tparams: tensor([  5.3227, -17.0502])\n",
      "Epoch: 2490,Loss: 2.933325\n",
      "\tgrad: tensor([-0.0076,  0.0433])\n",
      "\tparams: tensor([  5.3228, -17.0506])\n",
      "Epoch: 2491,Loss: 2.933306\n",
      "\tgrad: tensor([-0.0076,  0.0432])\n",
      "\tparams: tensor([  5.3229, -17.0510])\n",
      "Epoch: 2492,Loss: 2.933287\n",
      "\tgrad: tensor([-0.0076,  0.0431])\n",
      "\tparams: tensor([  5.3230, -17.0515])\n",
      "Epoch: 2493,Loss: 2.933266\n",
      "\tgrad: tensor([-0.0076,  0.0430])\n",
      "\tparams: tensor([  5.3230, -17.0519])\n",
      "Epoch: 2494,Loss: 2.933249\n",
      "\tgrad: tensor([-0.0076,  0.0430])\n",
      "\tparams: tensor([  5.3231, -17.0523])\n",
      "Epoch: 2495,Loss: 2.933229\n",
      "\tgrad: tensor([-0.0076,  0.0429])\n",
      "\tparams: tensor([  5.3232, -17.0527])\n",
      "Epoch: 2496,Loss: 2.933209\n",
      "\tgrad: tensor([-0.0076,  0.0428])\n",
      "\tparams: tensor([  5.3233, -17.0532])\n",
      "Epoch: 2497,Loss: 2.933190\n",
      "\tgrad: tensor([-0.0075,  0.0427])\n",
      "\tparams: tensor([  5.3233, -17.0536])\n",
      "Epoch: 2498,Loss: 2.933172\n",
      "\tgrad: tensor([-0.0075,  0.0427])\n",
      "\tparams: tensor([  5.3234, -17.0540])\n",
      "Epoch: 2499,Loss: 2.933154\n",
      "\tgrad: tensor([-0.0075,  0.0426])\n",
      "\tparams: tensor([  5.3235, -17.0544])\n",
      "Epoch: 2500,Loss: 2.933134\n",
      "\tgrad: tensor([-0.0075,  0.0425])\n",
      "\tparams: tensor([  5.3236, -17.0549])\n",
      "Epoch: 2501,Loss: 2.933116\n",
      "\tgrad: tensor([-0.0075,  0.0425])\n",
      "\tparams: tensor([  5.3236, -17.0553])\n",
      "Epoch: 2502,Loss: 2.933097\n",
      "\tgrad: tensor([-0.0075,  0.0424])\n",
      "\tparams: tensor([  5.3237, -17.0557])\n",
      "Epoch: 2503,Loss: 2.933079\n",
      "\tgrad: tensor([-0.0075,  0.0423])\n",
      "\tparams: tensor([  5.3238, -17.0561])\n",
      "Epoch: 2504,Loss: 2.933060\n",
      "\tgrad: tensor([-0.0075,  0.0422])\n",
      "\tparams: tensor([  5.3239, -17.0566])\n",
      "Epoch: 2505,Loss: 2.933043\n",
      "\tgrad: tensor([-0.0074,  0.0422])\n",
      "\tparams: tensor([  5.3239, -17.0570])\n",
      "Epoch: 2506,Loss: 2.933025\n",
      "\tgrad: tensor([-0.0074,  0.0421])\n",
      "\tparams: tensor([  5.3240, -17.0574])\n",
      "Epoch: 2507,Loss: 2.933007\n",
      "\tgrad: tensor([-0.0074,  0.0420])\n",
      "\tparams: tensor([  5.3241, -17.0578])\n",
      "Epoch: 2508,Loss: 2.932988\n",
      "\tgrad: tensor([-0.0074,  0.0420])\n",
      "\tparams: tensor([  5.3242, -17.0582])\n",
      "Epoch: 2509,Loss: 2.932970\n",
      "\tgrad: tensor([-0.0074,  0.0419])\n",
      "\tparams: tensor([  5.3242, -17.0587])\n",
      "Epoch: 2510,Loss: 2.932953\n",
      "\tgrad: tensor([-0.0074,  0.0418])\n",
      "\tparams: tensor([  5.3243, -17.0591])\n",
      "Epoch: 2511,Loss: 2.932932\n",
      "\tgrad: tensor([-0.0074,  0.0417])\n",
      "\tparams: tensor([  5.3244, -17.0595])\n",
      "Epoch: 2512,Loss: 2.932915\n",
      "\tgrad: tensor([-0.0073,  0.0417])\n",
      "\tparams: tensor([  5.3245, -17.0599])\n",
      "Epoch: 2513,Loss: 2.932898\n",
      "\tgrad: tensor([-0.0073,  0.0416])\n",
      "\tparams: tensor([  5.3245, -17.0603])\n",
      "Epoch: 2514,Loss: 2.932880\n",
      "\tgrad: tensor([-0.0073,  0.0415])\n",
      "\tparams: tensor([  5.3246, -17.0608])\n",
      "Epoch: 2515,Loss: 2.932862\n",
      "\tgrad: tensor([-0.0073,  0.0415])\n",
      "\tparams: tensor([  5.3247, -17.0612])\n",
      "Epoch: 2516,Loss: 2.932846\n",
      "\tgrad: tensor([-0.0073,  0.0414])\n",
      "\tparams: tensor([  5.3248, -17.0616])\n",
      "Epoch: 2517,Loss: 2.932826\n",
      "\tgrad: tensor([-0.0073,  0.0413])\n",
      "\tparams: tensor([  5.3248, -17.0620])\n",
      "Epoch: 2518,Loss: 2.932810\n",
      "\tgrad: tensor([-0.0073,  0.0412])\n",
      "\tparams: tensor([  5.3249, -17.0624])\n",
      "Epoch: 2519,Loss: 2.932790\n",
      "\tgrad: tensor([-0.0073,  0.0412])\n",
      "\tparams: tensor([  5.3250, -17.0628])\n",
      "Epoch: 2520,Loss: 2.932774\n",
      "\tgrad: tensor([-0.0073,  0.0411])\n",
      "\tparams: tensor([  5.3250, -17.0632])\n",
      "Epoch: 2521,Loss: 2.932758\n",
      "\tgrad: tensor([-0.0073,  0.0410])\n",
      "\tparams: tensor([  5.3251, -17.0636])\n",
      "Epoch: 2522,Loss: 2.932739\n",
      "\tgrad: tensor([-0.0073,  0.0410])\n",
      "\tparams: tensor([  5.3252, -17.0640])\n",
      "Epoch: 2523,Loss: 2.932723\n",
      "\tgrad: tensor([-0.0072,  0.0409])\n",
      "\tparams: tensor([  5.3253, -17.0645])\n",
      "Epoch: 2524,Loss: 2.932706\n",
      "\tgrad: tensor([-0.0072,  0.0408])\n",
      "\tparams: tensor([  5.3253, -17.0649])\n",
      "Epoch: 2525,Loss: 2.932689\n",
      "\tgrad: tensor([-0.0072,  0.0408])\n",
      "\tparams: tensor([  5.3254, -17.0653])\n",
      "Epoch: 2526,Loss: 2.932671\n",
      "\tgrad: tensor([-0.0072,  0.0407])\n",
      "\tparams: tensor([  5.3255, -17.0657])\n",
      "Epoch: 2527,Loss: 2.932654\n",
      "\tgrad: tensor([-0.0072,  0.0406])\n",
      "\tparams: tensor([  5.3256, -17.0661])\n",
      "Epoch: 2528,Loss: 2.932637\n",
      "\tgrad: tensor([-0.0072,  0.0405])\n",
      "\tparams: tensor([  5.3256, -17.0665])\n",
      "Epoch: 2529,Loss: 2.932619\n",
      "\tgrad: tensor([-0.0072,  0.0405])\n",
      "\tparams: tensor([  5.3257, -17.0669])\n",
      "Epoch: 2530,Loss: 2.932603\n",
      "\tgrad: tensor([-0.0071,  0.0404])\n",
      "\tparams: tensor([  5.3258, -17.0673])\n",
      "Epoch: 2531,Loss: 2.932585\n",
      "\tgrad: tensor([-0.0071,  0.0403])\n",
      "\tparams: tensor([  5.3258, -17.0677])\n",
      "Epoch: 2532,Loss: 2.932569\n",
      "\tgrad: tensor([-0.0071,  0.0403])\n",
      "\tparams: tensor([  5.3259, -17.0681])\n",
      "Epoch: 2533,Loss: 2.932553\n",
      "\tgrad: tensor([-0.0071,  0.0402])\n",
      "\tparams: tensor([  5.3260, -17.0685])\n",
      "Epoch: 2534,Loss: 2.932535\n",
      "\tgrad: tensor([-0.0071,  0.0401])\n",
      "\tparams: tensor([  5.3261, -17.0689])\n",
      "Epoch: 2535,Loss: 2.932520\n",
      "\tgrad: tensor([-0.0071,  0.0401])\n",
      "\tparams: tensor([  5.3261, -17.0693])\n",
      "Epoch: 2536,Loss: 2.932502\n",
      "\tgrad: tensor([-0.0071,  0.0400])\n",
      "\tparams: tensor([  5.3262, -17.0697])\n",
      "Epoch: 2537,Loss: 2.932487\n",
      "\tgrad: tensor([-0.0071,  0.0399])\n",
      "\tparams: tensor([  5.3263, -17.0701])\n",
      "Epoch: 2538,Loss: 2.932469\n",
      "\tgrad: tensor([-0.0070,  0.0399])\n",
      "\tparams: tensor([  5.3263, -17.0705])\n",
      "Epoch: 2539,Loss: 2.932455\n",
      "\tgrad: tensor([-0.0070,  0.0398])\n",
      "\tparams: tensor([  5.3264, -17.0709])\n",
      "Epoch: 2540,Loss: 2.932438\n",
      "\tgrad: tensor([-0.0070,  0.0397])\n",
      "\tparams: tensor([  5.3265, -17.0713])\n",
      "Epoch: 2541,Loss: 2.932421\n",
      "\tgrad: tensor([-0.0070,  0.0397])\n",
      "\tparams: tensor([  5.3265, -17.0717])\n",
      "Epoch: 2542,Loss: 2.932404\n",
      "\tgrad: tensor([-0.0070,  0.0396])\n",
      "\tparams: tensor([  5.3266, -17.0721])\n",
      "Epoch: 2543,Loss: 2.932387\n",
      "\tgrad: tensor([-0.0070,  0.0395])\n",
      "\tparams: tensor([  5.3267, -17.0725])\n",
      "Epoch: 2544,Loss: 2.932371\n",
      "\tgrad: tensor([-0.0070,  0.0395])\n",
      "\tparams: tensor([  5.3268, -17.0729])\n",
      "Epoch: 2545,Loss: 2.932358\n",
      "\tgrad: tensor([-0.0070,  0.0394])\n",
      "\tparams: tensor([  5.3268, -17.0733])\n",
      "Epoch: 2546,Loss: 2.932340\n",
      "\tgrad: tensor([-0.0069,  0.0393])\n",
      "\tparams: tensor([  5.3269, -17.0737])\n",
      "Epoch: 2547,Loss: 2.932324\n",
      "\tgrad: tensor([-0.0069,  0.0393])\n",
      "\tparams: tensor([  5.3270, -17.0741])\n",
      "Epoch: 2548,Loss: 2.932310\n",
      "\tgrad: tensor([-0.0069,  0.0392])\n",
      "\tparams: tensor([  5.3270, -17.0745])\n",
      "Epoch: 2549,Loss: 2.932293\n",
      "\tgrad: tensor([-0.0069,  0.0391])\n",
      "\tparams: tensor([  5.3271, -17.0749])\n",
      "Epoch: 2550,Loss: 2.932277\n",
      "\tgrad: tensor([-0.0069,  0.0391])\n",
      "\tparams: tensor([  5.3272, -17.0752])\n",
      "Epoch: 2551,Loss: 2.932261\n",
      "\tgrad: tensor([-0.0069,  0.0390])\n",
      "\tparams: tensor([  5.3272, -17.0756])\n",
      "Epoch: 2552,Loss: 2.932246\n",
      "\tgrad: tensor([-0.0069,  0.0389])\n",
      "\tparams: tensor([  5.3273, -17.0760])\n",
      "Epoch: 2553,Loss: 2.932229\n",
      "\tgrad: tensor([-0.0069,  0.0389])\n",
      "\tparams: tensor([  5.3274, -17.0764])\n",
      "Epoch: 2554,Loss: 2.932215\n",
      "\tgrad: tensor([-0.0069,  0.0388])\n",
      "\tparams: tensor([  5.3274, -17.0768])\n",
      "Epoch: 2555,Loss: 2.932198\n",
      "\tgrad: tensor([-0.0068,  0.0387])\n",
      "\tparams: tensor([  5.3275, -17.0772])\n",
      "Epoch: 2556,Loss: 2.932183\n",
      "\tgrad: tensor([-0.0068,  0.0387])\n",
      "\tparams: tensor([  5.3276, -17.0776])\n",
      "Epoch: 2557,Loss: 2.932167\n",
      "\tgrad: tensor([-0.0068,  0.0386])\n",
      "\tparams: tensor([  5.3276, -17.0780])\n",
      "Epoch: 2558,Loss: 2.932153\n",
      "\tgrad: tensor([-0.0068,  0.0385])\n",
      "\tparams: tensor([  5.3277, -17.0783])\n",
      "Epoch: 2559,Loss: 2.932137\n",
      "\tgrad: tensor([-0.0068,  0.0385])\n",
      "\tparams: tensor([  5.3278, -17.0787])\n",
      "Epoch: 2560,Loss: 2.932122\n",
      "\tgrad: tensor([-0.0068,  0.0384])\n",
      "\tparams: tensor([  5.3279, -17.0791])\n",
      "Epoch: 2561,Loss: 2.932107\n",
      "\tgrad: tensor([-0.0068,  0.0383])\n",
      "\tparams: tensor([  5.3279, -17.0795])\n",
      "Epoch: 2562,Loss: 2.932092\n",
      "\tgrad: tensor([-0.0068,  0.0383])\n",
      "\tparams: tensor([  5.3280, -17.0799])\n",
      "Epoch: 2563,Loss: 2.932076\n",
      "\tgrad: tensor([-0.0067,  0.0382])\n",
      "\tparams: tensor([  5.3281, -17.0803])\n",
      "Epoch: 2564,Loss: 2.932061\n",
      "\tgrad: tensor([-0.0067,  0.0381])\n",
      "\tparams: tensor([  5.3281, -17.0806])\n",
      "Epoch: 2565,Loss: 2.932047\n",
      "\tgrad: tensor([-0.0067,  0.0381])\n",
      "\tparams: tensor([  5.3282, -17.0810])\n",
      "Epoch: 2566,Loss: 2.932031\n",
      "\tgrad: tensor([-0.0067,  0.0380])\n",
      "\tparams: tensor([  5.3283, -17.0814])\n",
      "Epoch: 2567,Loss: 2.932017\n",
      "\tgrad: tensor([-0.0067,  0.0379])\n",
      "\tparams: tensor([  5.3283, -17.0818])\n",
      "Epoch: 2568,Loss: 2.932002\n",
      "\tgrad: tensor([-0.0067,  0.0379])\n",
      "\tparams: tensor([  5.3284, -17.0822])\n",
      "Epoch: 2569,Loss: 2.931986\n",
      "\tgrad: tensor([-0.0067,  0.0378])\n",
      "\tparams: tensor([  5.3285, -17.0825])\n",
      "Epoch: 2570,Loss: 2.931972\n",
      "\tgrad: tensor([-0.0067,  0.0378])\n",
      "\tparams: tensor([  5.3285, -17.0829])\n",
      "Epoch: 2571,Loss: 2.931957\n",
      "\tgrad: tensor([-0.0067,  0.0377])\n",
      "\tparams: tensor([  5.3286, -17.0833])\n",
      "Epoch: 2572,Loss: 2.931941\n",
      "\tgrad: tensor([-0.0067,  0.0376])\n",
      "\tparams: tensor([  5.3287, -17.0837])\n",
      "Epoch: 2573,Loss: 2.931929\n",
      "\tgrad: tensor([-0.0066,  0.0376])\n",
      "\tparams: tensor([  5.3287, -17.0840])\n",
      "Epoch: 2574,Loss: 2.931914\n",
      "\tgrad: tensor([-0.0066,  0.0375])\n",
      "\tparams: tensor([  5.3288, -17.0844])\n",
      "Epoch: 2575,Loss: 2.931900\n",
      "\tgrad: tensor([-0.0066,  0.0374])\n",
      "\tparams: tensor([  5.3289, -17.0848])\n",
      "Epoch: 2576,Loss: 2.931885\n",
      "\tgrad: tensor([-0.0066,  0.0374])\n",
      "\tparams: tensor([  5.3289, -17.0852])\n",
      "Epoch: 2577,Loss: 2.931870\n",
      "\tgrad: tensor([-0.0066,  0.0373])\n",
      "\tparams: tensor([  5.3290, -17.0855])\n",
      "Epoch: 2578,Loss: 2.931855\n",
      "\tgrad: tensor([-0.0066,  0.0372])\n",
      "\tparams: tensor([  5.3291, -17.0859])\n",
      "Epoch: 2579,Loss: 2.931842\n",
      "\tgrad: tensor([-0.0066,  0.0372])\n",
      "\tparams: tensor([  5.3291, -17.0863])\n",
      "Epoch: 2580,Loss: 2.931828\n",
      "\tgrad: tensor([-0.0066,  0.0371])\n",
      "\tparams: tensor([  5.3292, -17.0867])\n",
      "Epoch: 2581,Loss: 2.931813\n",
      "\tgrad: tensor([-0.0065,  0.0371])\n",
      "\tparams: tensor([  5.3293, -17.0870])\n",
      "Epoch: 2582,Loss: 2.931799\n",
      "\tgrad: tensor([-0.0065,  0.0370])\n",
      "\tparams: tensor([  5.3293, -17.0874])\n",
      "Epoch: 2583,Loss: 2.931786\n",
      "\tgrad: tensor([-0.0065,  0.0369])\n",
      "\tparams: tensor([  5.3294, -17.0878])\n",
      "Epoch: 2584,Loss: 2.931771\n",
      "\tgrad: tensor([-0.0065,  0.0369])\n",
      "\tparams: tensor([  5.3294, -17.0881])\n",
      "Epoch: 2585,Loss: 2.931759\n",
      "\tgrad: tensor([-0.0065,  0.0368])\n",
      "\tparams: tensor([  5.3295, -17.0885])\n",
      "Epoch: 2586,Loss: 2.931742\n",
      "\tgrad: tensor([-0.0065,  0.0367])\n",
      "\tparams: tensor([  5.3296, -17.0889])\n",
      "Epoch: 2587,Loss: 2.931729\n",
      "\tgrad: tensor([-0.0065,  0.0367])\n",
      "\tparams: tensor([  5.3296, -17.0892])\n",
      "Epoch: 2588,Loss: 2.931717\n",
      "\tgrad: tensor([-0.0065,  0.0366])\n",
      "\tparams: tensor([  5.3297, -17.0896])\n",
      "Epoch: 2589,Loss: 2.931701\n",
      "\tgrad: tensor([-0.0065,  0.0366])\n",
      "\tparams: tensor([  5.3298, -17.0900])\n",
      "Epoch: 2590,Loss: 2.931687\n",
      "\tgrad: tensor([-0.0065,  0.0365])\n",
      "\tparams: tensor([  5.3298, -17.0903])\n",
      "Epoch: 2591,Loss: 2.931674\n",
      "\tgrad: tensor([-0.0064,  0.0364])\n",
      "\tparams: tensor([  5.3299, -17.0907])\n",
      "Epoch: 2592,Loss: 2.931660\n",
      "\tgrad: tensor([-0.0064,  0.0364])\n",
      "\tparams: tensor([  5.3300, -17.0911])\n",
      "Epoch: 2593,Loss: 2.931648\n",
      "\tgrad: tensor([-0.0064,  0.0363])\n",
      "\tparams: tensor([  5.3300, -17.0914])\n",
      "Epoch: 2594,Loss: 2.931632\n",
      "\tgrad: tensor([-0.0064,  0.0362])\n",
      "\tparams: tensor([  5.3301, -17.0918])\n",
      "Epoch: 2595,Loss: 2.931619\n",
      "\tgrad: tensor([-0.0064,  0.0362])\n",
      "\tparams: tensor([  5.3302, -17.0921])\n",
      "Epoch: 2596,Loss: 2.931606\n",
      "\tgrad: tensor([-0.0064,  0.0361])\n",
      "\tparams: tensor([  5.3302, -17.0925])\n",
      "Epoch: 2597,Loss: 2.931593\n",
      "\tgrad: tensor([-0.0064,  0.0361])\n",
      "\tparams: tensor([  5.3303, -17.0929])\n",
      "Epoch: 2598,Loss: 2.931580\n",
      "\tgrad: tensor([-0.0064,  0.0360])\n",
      "\tparams: tensor([  5.3303, -17.0932])\n",
      "Epoch: 2599,Loss: 2.931566\n",
      "\tgrad: tensor([-0.0064,  0.0359])\n",
      "\tparams: tensor([  5.3304, -17.0936])\n",
      "Epoch: 2600,Loss: 2.931554\n",
      "\tgrad: tensor([-0.0064,  0.0359])\n",
      "\tparams: tensor([  5.3305, -17.0939])\n",
      "Epoch: 2601,Loss: 2.931538\n",
      "\tgrad: tensor([-0.0063,  0.0358])\n",
      "\tparams: tensor([  5.3305, -17.0943])\n",
      "Epoch: 2602,Loss: 2.931526\n",
      "\tgrad: tensor([-0.0063,  0.0358])\n",
      "\tparams: tensor([  5.3306, -17.0947])\n",
      "Epoch: 2603,Loss: 2.931512\n",
      "\tgrad: tensor([-0.0063,  0.0357])\n",
      "\tparams: tensor([  5.3307, -17.0950])\n",
      "Epoch: 2604,Loss: 2.931499\n",
      "\tgrad: tensor([-0.0063,  0.0356])\n",
      "\tparams: tensor([  5.3307, -17.0954])\n",
      "Epoch: 2605,Loss: 2.931488\n",
      "\tgrad: tensor([-0.0063,  0.0356])\n",
      "\tparams: tensor([  5.3308, -17.0957])\n",
      "Epoch: 2606,Loss: 2.931474\n",
      "\tgrad: tensor([-0.0063,  0.0355])\n",
      "\tparams: tensor([  5.3309, -17.0961])\n",
      "Epoch: 2607,Loss: 2.931462\n",
      "\tgrad: tensor([-0.0062,  0.0355])\n",
      "\tparams: tensor([  5.3309, -17.0964])\n",
      "Epoch: 2608,Loss: 2.931448\n",
      "\tgrad: tensor([-0.0062,  0.0354])\n",
      "\tparams: tensor([  5.3310, -17.0968])\n",
      "Epoch: 2609,Loss: 2.931436\n",
      "\tgrad: tensor([-0.0062,  0.0353])\n",
      "\tparams: tensor([  5.3310, -17.0971])\n",
      "Epoch: 2610,Loss: 2.931423\n",
      "\tgrad: tensor([-0.0062,  0.0353])\n",
      "\tparams: tensor([  5.3311, -17.0975])\n",
      "Epoch: 2611,Loss: 2.931411\n",
      "\tgrad: tensor([-0.0062,  0.0352])\n",
      "\tparams: tensor([  5.3312, -17.0979])\n",
      "Epoch: 2612,Loss: 2.931397\n",
      "\tgrad: tensor([-0.0062,  0.0352])\n",
      "\tparams: tensor([  5.3312, -17.0982])\n",
      "Epoch: 2613,Loss: 2.931384\n",
      "\tgrad: tensor([-0.0062,  0.0351])\n",
      "\tparams: tensor([  5.3313, -17.0986])\n",
      "Epoch: 2614,Loss: 2.931371\n",
      "\tgrad: tensor([-0.0062,  0.0350])\n",
      "\tparams: tensor([  5.3313, -17.0989])\n",
      "Epoch: 2615,Loss: 2.931358\n",
      "\tgrad: tensor([-0.0062,  0.0350])\n",
      "\tparams: tensor([  5.3314, -17.0993])\n",
      "Epoch: 2616,Loss: 2.931346\n",
      "\tgrad: tensor([-0.0062,  0.0349])\n",
      "\tparams: tensor([  5.3315, -17.0996])\n",
      "Epoch: 2617,Loss: 2.931335\n",
      "\tgrad: tensor([-0.0062,  0.0349])\n",
      "\tparams: tensor([  5.3315, -17.1000])\n",
      "Epoch: 2618,Loss: 2.931322\n",
      "\tgrad: tensor([-0.0062,  0.0348])\n",
      "\tparams: tensor([  5.3316, -17.1003])\n",
      "Epoch: 2619,Loss: 2.931308\n",
      "\tgrad: tensor([-0.0061,  0.0347])\n",
      "\tparams: tensor([  5.3317, -17.1006])\n",
      "Epoch: 2620,Loss: 2.931296\n",
      "\tgrad: tensor([-0.0061,  0.0347])\n",
      "\tparams: tensor([  5.3317, -17.1010])\n",
      "Epoch: 2621,Loss: 2.931282\n",
      "\tgrad: tensor([-0.0061,  0.0346])\n",
      "\tparams: tensor([  5.3318, -17.1013])\n",
      "Epoch: 2622,Loss: 2.931272\n",
      "\tgrad: tensor([-0.0061,  0.0346])\n",
      "\tparams: tensor([  5.3318, -17.1017])\n",
      "Epoch: 2623,Loss: 2.931258\n",
      "\tgrad: tensor([-0.0061,  0.0345])\n",
      "\tparams: tensor([  5.3319, -17.1020])\n",
      "Epoch: 2624,Loss: 2.931245\n",
      "\tgrad: tensor([-0.0061,  0.0344])\n",
      "\tparams: tensor([  5.3320, -17.1024])\n",
      "Epoch: 2625,Loss: 2.931234\n",
      "\tgrad: tensor([-0.0061,  0.0344])\n",
      "\tparams: tensor([  5.3320, -17.1027])\n",
      "Epoch: 2626,Loss: 2.931222\n",
      "\tgrad: tensor([-0.0061,  0.0343])\n",
      "\tparams: tensor([  5.3321, -17.1031])\n",
      "Epoch: 2627,Loss: 2.931211\n",
      "\tgrad: tensor([-0.0060,  0.0343])\n",
      "\tparams: tensor([  5.3321, -17.1034])\n",
      "Epoch: 2628,Loss: 2.931196\n",
      "\tgrad: tensor([-0.0060,  0.0342])\n",
      "\tparams: tensor([  5.3322, -17.1038])\n",
      "Epoch: 2629,Loss: 2.931185\n",
      "\tgrad: tensor([-0.0060,  0.0342])\n",
      "\tparams: tensor([  5.3323, -17.1041])\n",
      "Epoch: 2630,Loss: 2.931173\n",
      "\tgrad: tensor([-0.0060,  0.0341])\n",
      "\tparams: tensor([  5.3323, -17.1044])\n",
      "Epoch: 2631,Loss: 2.931162\n",
      "\tgrad: tensor([-0.0060,  0.0340])\n",
      "\tparams: tensor([  5.3324, -17.1048])\n",
      "Epoch: 2632,Loss: 2.931149\n",
      "\tgrad: tensor([-0.0060,  0.0340])\n",
      "\tparams: tensor([  5.3324, -17.1051])\n",
      "Epoch: 2633,Loss: 2.931138\n",
      "\tgrad: tensor([-0.0060,  0.0339])\n",
      "\tparams: tensor([  5.3325, -17.1055])\n",
      "Epoch: 2634,Loss: 2.931126\n",
      "\tgrad: tensor([-0.0060,  0.0339])\n",
      "\tparams: tensor([  5.3326, -17.1058])\n",
      "Epoch: 2635,Loss: 2.931114\n",
      "\tgrad: tensor([-0.0060,  0.0338])\n",
      "\tparams: tensor([  5.3326, -17.1061])\n",
      "Epoch: 2636,Loss: 2.931101\n",
      "\tgrad: tensor([-0.0060,  0.0337])\n",
      "\tparams: tensor([  5.3327, -17.1065])\n",
      "Epoch: 2637,Loss: 2.931090\n",
      "\tgrad: tensor([-0.0059,  0.0337])\n",
      "\tparams: tensor([  5.3327, -17.1068])\n",
      "Epoch: 2638,Loss: 2.931079\n",
      "\tgrad: tensor([-0.0059,  0.0336])\n",
      "\tparams: tensor([  5.3328, -17.1071])\n",
      "Epoch: 2639,Loss: 2.931067\n",
      "\tgrad: tensor([-0.0059,  0.0336])\n",
      "\tparams: tensor([  5.3329, -17.1075])\n",
      "Epoch: 2640,Loss: 2.931054\n",
      "\tgrad: tensor([-0.0059,  0.0335])\n",
      "\tparams: tensor([  5.3329, -17.1078])\n",
      "Epoch: 2641,Loss: 2.931044\n",
      "\tgrad: tensor([-0.0059,  0.0335])\n",
      "\tparams: tensor([  5.3330, -17.1081])\n",
      "Epoch: 2642,Loss: 2.931034\n",
      "\tgrad: tensor([-0.0059,  0.0334])\n",
      "\tparams: tensor([  5.3330, -17.1085])\n",
      "Epoch: 2643,Loss: 2.931021\n",
      "\tgrad: tensor([-0.0059,  0.0333])\n",
      "\tparams: tensor([  5.3331, -17.1088])\n",
      "Epoch: 2644,Loss: 2.931010\n",
      "\tgrad: tensor([-0.0059,  0.0333])\n",
      "\tparams: tensor([  5.3332, -17.1091])\n",
      "Epoch: 2645,Loss: 2.930999\n",
      "\tgrad: tensor([-0.0059,  0.0332])\n",
      "\tparams: tensor([  5.3332, -17.1095])\n",
      "Epoch: 2646,Loss: 2.930987\n",
      "\tgrad: tensor([-0.0059,  0.0332])\n",
      "\tparams: tensor([  5.3333, -17.1098])\n",
      "Epoch: 2647,Loss: 2.930976\n",
      "\tgrad: tensor([-0.0059,  0.0331])\n",
      "\tparams: tensor([  5.3333, -17.1101])\n",
      "Epoch: 2648,Loss: 2.930964\n",
      "\tgrad: tensor([-0.0059,  0.0331])\n",
      "\tparams: tensor([  5.3334, -17.1105])\n",
      "Epoch: 2649,Loss: 2.930953\n",
      "\tgrad: tensor([-0.0058,  0.0330])\n",
      "\tparams: tensor([  5.3335, -17.1108])\n",
      "Epoch: 2650,Loss: 2.930941\n",
      "\tgrad: tensor([-0.0058,  0.0330])\n",
      "\tparams: tensor([  5.3335, -17.1111])\n",
      "Epoch: 2651,Loss: 2.930932\n",
      "\tgrad: tensor([-0.0058,  0.0329])\n",
      "\tparams: tensor([  5.3336, -17.1115])\n",
      "Epoch: 2652,Loss: 2.930921\n",
      "\tgrad: tensor([-0.0058,  0.0328])\n",
      "\tparams: tensor([  5.3336, -17.1118])\n",
      "Epoch: 2653,Loss: 2.930908\n",
      "\tgrad: tensor([-0.0058,  0.0328])\n",
      "\tparams: tensor([  5.3337, -17.1121])\n",
      "Epoch: 2654,Loss: 2.930899\n",
      "\tgrad: tensor([-0.0058,  0.0327])\n",
      "\tparams: tensor([  5.3337, -17.1124])\n",
      "Epoch: 2655,Loss: 2.930885\n",
      "\tgrad: tensor([-0.0058,  0.0327])\n",
      "\tparams: tensor([  5.3338, -17.1128])\n",
      "Epoch: 2656,Loss: 2.930876\n",
      "\tgrad: tensor([-0.0058,  0.0326])\n",
      "\tparams: tensor([  5.3339, -17.1131])\n",
      "Epoch: 2657,Loss: 2.930863\n",
      "\tgrad: tensor([-0.0057,  0.0326])\n",
      "\tparams: tensor([  5.3339, -17.1134])\n",
      "Epoch: 2658,Loss: 2.930854\n",
      "\tgrad: tensor([-0.0057,  0.0325])\n",
      "\tparams: tensor([  5.3340, -17.1137])\n",
      "Epoch: 2659,Loss: 2.930841\n",
      "\tgrad: tensor([-0.0057,  0.0325])\n",
      "\tparams: tensor([  5.3340, -17.1141])\n",
      "Epoch: 2660,Loss: 2.930833\n",
      "\tgrad: tensor([-0.0057,  0.0324])\n",
      "\tparams: tensor([  5.3341, -17.1144])\n",
      "Epoch: 2661,Loss: 2.930821\n",
      "\tgrad: tensor([-0.0057,  0.0323])\n",
      "\tparams: tensor([  5.3341, -17.1147])\n",
      "Epoch: 2662,Loss: 2.930811\n",
      "\tgrad: tensor([-0.0057,  0.0323])\n",
      "\tparams: tensor([  5.3342, -17.1150])\n",
      "Epoch: 2663,Loss: 2.930801\n",
      "\tgrad: tensor([-0.0057,  0.0322])\n",
      "\tparams: tensor([  5.3343, -17.1154])\n",
      "Epoch: 2664,Loss: 2.930788\n",
      "\tgrad: tensor([-0.0057,  0.0322])\n",
      "\tparams: tensor([  5.3343, -17.1157])\n",
      "Epoch: 2665,Loss: 2.930778\n",
      "\tgrad: tensor([-0.0057,  0.0321])\n",
      "\tparams: tensor([  5.3344, -17.1160])\n",
      "Epoch: 2666,Loss: 2.930767\n",
      "\tgrad: tensor([-0.0057,  0.0321])\n",
      "\tparams: tensor([  5.3344, -17.1163])\n",
      "Epoch: 2667,Loss: 2.930757\n",
      "\tgrad: tensor([-0.0057,  0.0320])\n",
      "\tparams: tensor([  5.3345, -17.1166])\n",
      "Epoch: 2668,Loss: 2.930746\n",
      "\tgrad: tensor([-0.0056,  0.0320])\n",
      "\tparams: tensor([  5.3345, -17.1170])\n",
      "Epoch: 2669,Loss: 2.930736\n",
      "\tgrad: tensor([-0.0056,  0.0319])\n",
      "\tparams: tensor([  5.3346, -17.1173])\n",
      "Epoch: 2670,Loss: 2.930724\n",
      "\tgrad: tensor([-0.0056,  0.0319])\n",
      "\tparams: tensor([  5.3347, -17.1176])\n",
      "Epoch: 2671,Loss: 2.930715\n",
      "\tgrad: tensor([-0.0056,  0.0318])\n",
      "\tparams: tensor([  5.3347, -17.1179])\n",
      "Epoch: 2672,Loss: 2.930704\n",
      "\tgrad: tensor([-0.0056,  0.0317])\n",
      "\tparams: tensor([  5.3348, -17.1182])\n",
      "Epoch: 2673,Loss: 2.930694\n",
      "\tgrad: tensor([-0.0056,  0.0317])\n",
      "\tparams: tensor([  5.3348, -17.1186])\n",
      "Epoch: 2674,Loss: 2.930685\n",
      "\tgrad: tensor([-0.0056,  0.0316])\n",
      "\tparams: tensor([  5.3349, -17.1189])\n",
      "Epoch: 2675,Loss: 2.930674\n",
      "\tgrad: tensor([-0.0056,  0.0316])\n",
      "\tparams: tensor([  5.3349, -17.1192])\n",
      "Epoch: 2676,Loss: 2.930663\n",
      "\tgrad: tensor([-0.0056,  0.0315])\n",
      "\tparams: tensor([  5.3350, -17.1195])\n",
      "Epoch: 2677,Loss: 2.930654\n",
      "\tgrad: tensor([-0.0056,  0.0315])\n",
      "\tparams: tensor([  5.3350, -17.1198])\n",
      "Epoch: 2678,Loss: 2.930644\n",
      "\tgrad: tensor([-0.0055,  0.0314])\n",
      "\tparams: tensor([  5.3351, -17.1201])\n",
      "Epoch: 2679,Loss: 2.930631\n",
      "\tgrad: tensor([-0.0055,  0.0314])\n",
      "\tparams: tensor([  5.3352, -17.1204])\n",
      "Epoch: 2680,Loss: 2.930621\n",
      "\tgrad: tensor([-0.0055,  0.0313])\n",
      "\tparams: tensor([  5.3352, -17.1208])\n",
      "Epoch: 2681,Loss: 2.930613\n",
      "\tgrad: tensor([-0.0055,  0.0313])\n",
      "\tparams: tensor([  5.3353, -17.1211])\n",
      "Epoch: 2682,Loss: 2.930603\n",
      "\tgrad: tensor([-0.0055,  0.0312])\n",
      "\tparams: tensor([  5.3353, -17.1214])\n",
      "Epoch: 2683,Loss: 2.930593\n",
      "\tgrad: tensor([-0.0055,  0.0312])\n",
      "\tparams: tensor([  5.3354, -17.1217])\n",
      "Epoch: 2684,Loss: 2.930582\n",
      "\tgrad: tensor([-0.0055,  0.0311])\n",
      "\tparams: tensor([  5.3354, -17.1220])\n",
      "Epoch: 2685,Loss: 2.930571\n",
      "\tgrad: tensor([-0.0055,  0.0310])\n",
      "\tparams: tensor([  5.3355, -17.1223])\n",
      "Epoch: 2686,Loss: 2.930562\n",
      "\tgrad: tensor([-0.0055,  0.0310])\n",
      "\tparams: tensor([  5.3355, -17.1226])\n",
      "Epoch: 2687,Loss: 2.930552\n",
      "\tgrad: tensor([-0.0055,  0.0309])\n",
      "\tparams: tensor([  5.3356, -17.1229])\n",
      "Epoch: 2688,Loss: 2.930543\n",
      "\tgrad: tensor([-0.0055,  0.0309])\n",
      "\tparams: tensor([  5.3356, -17.1232])\n",
      "Epoch: 2689,Loss: 2.930534\n",
      "\tgrad: tensor([-0.0055,  0.0308])\n",
      "\tparams: tensor([  5.3357, -17.1236])\n",
      "Epoch: 2690,Loss: 2.930523\n",
      "\tgrad: tensor([-0.0054,  0.0308])\n",
      "\tparams: tensor([  5.3358, -17.1239])\n",
      "Epoch: 2691,Loss: 2.930514\n",
      "\tgrad: tensor([-0.0054,  0.0307])\n",
      "\tparams: tensor([  5.3358, -17.1242])\n",
      "Epoch: 2692,Loss: 2.930502\n",
      "\tgrad: tensor([-0.0054,  0.0307])\n",
      "\tparams: tensor([  5.3359, -17.1245])\n",
      "Epoch: 2693,Loss: 2.930493\n",
      "\tgrad: tensor([-0.0054,  0.0306])\n",
      "\tparams: tensor([  5.3359, -17.1248])\n",
      "Epoch: 2694,Loss: 2.930482\n",
      "\tgrad: tensor([-0.0054,  0.0306])\n",
      "\tparams: tensor([  5.3360, -17.1251])\n",
      "Epoch: 2695,Loss: 2.930474\n",
      "\tgrad: tensor([-0.0054,  0.0305])\n",
      "\tparams: tensor([  5.3360, -17.1254])\n",
      "Epoch: 2696,Loss: 2.930464\n",
      "\tgrad: tensor([-0.0054,  0.0305])\n",
      "\tparams: tensor([  5.3361, -17.1257])\n",
      "Epoch: 2697,Loss: 2.930454\n",
      "\tgrad: tensor([-0.0054,  0.0304])\n",
      "\tparams: tensor([  5.3361, -17.1260])\n",
      "Epoch: 2698,Loss: 2.930445\n",
      "\tgrad: tensor([-0.0054,  0.0304])\n",
      "\tparams: tensor([  5.3362, -17.1263])\n",
      "Epoch: 2699,Loss: 2.930436\n",
      "\tgrad: tensor([-0.0054,  0.0303])\n",
      "\tparams: tensor([  5.3362, -17.1266])\n",
      "Epoch: 2700,Loss: 2.930426\n",
      "\tgrad: tensor([-0.0054,  0.0303])\n",
      "\tparams: tensor([  5.3363, -17.1269])\n",
      "Epoch: 2701,Loss: 2.930416\n",
      "\tgrad: tensor([-0.0054,  0.0302])\n",
      "\tparams: tensor([  5.3364, -17.1272])\n",
      "Epoch: 2702,Loss: 2.930408\n",
      "\tgrad: tensor([-0.0053,  0.0302])\n",
      "\tparams: tensor([  5.3364, -17.1275])\n",
      "Epoch: 2703,Loss: 2.930398\n",
      "\tgrad: tensor([-0.0053,  0.0301])\n",
      "\tparams: tensor([  5.3365, -17.1278])\n",
      "Epoch: 2704,Loss: 2.930388\n",
      "\tgrad: tensor([-0.0053,  0.0301])\n",
      "\tparams: tensor([  5.3365, -17.1281])\n",
      "Epoch: 2705,Loss: 2.930380\n",
      "\tgrad: tensor([-0.0053,  0.0300])\n",
      "\tparams: tensor([  5.3366, -17.1284])\n",
      "Epoch: 2706,Loss: 2.930370\n",
      "\tgrad: tensor([-0.0053,  0.0300])\n",
      "\tparams: tensor([  5.3366, -17.1287])\n",
      "Epoch: 2707,Loss: 2.930360\n",
      "\tgrad: tensor([-0.0053,  0.0299])\n",
      "\tparams: tensor([  5.3367, -17.1290])\n",
      "Epoch: 2708,Loss: 2.930353\n",
      "\tgrad: tensor([-0.0053,  0.0299])\n",
      "\tparams: tensor([  5.3367, -17.1293])\n",
      "Epoch: 2709,Loss: 2.930342\n",
      "\tgrad: tensor([-0.0053,  0.0298])\n",
      "\tparams: tensor([  5.3368, -17.1296])\n",
      "Epoch: 2710,Loss: 2.930335\n",
      "\tgrad: tensor([-0.0053,  0.0298])\n",
      "\tparams: tensor([  5.3368, -17.1299])\n",
      "Epoch: 2711,Loss: 2.930325\n",
      "\tgrad: tensor([-0.0053,  0.0297])\n",
      "\tparams: tensor([  5.3369, -17.1302])\n",
      "Epoch: 2712,Loss: 2.930315\n",
      "\tgrad: tensor([-0.0053,  0.0297])\n",
      "\tparams: tensor([  5.3369, -17.1305])\n",
      "Epoch: 2713,Loss: 2.930306\n",
      "\tgrad: tensor([-0.0052,  0.0296])\n",
      "\tparams: tensor([  5.3370, -17.1308])\n",
      "Epoch: 2714,Loss: 2.930298\n",
      "\tgrad: tensor([-0.0052,  0.0296])\n",
      "\tparams: tensor([  5.3370, -17.1311])\n",
      "Epoch: 2715,Loss: 2.930288\n",
      "\tgrad: tensor([-0.0052,  0.0295])\n",
      "\tparams: tensor([  5.3371, -17.1314])\n",
      "Epoch: 2716,Loss: 2.930279\n",
      "\tgrad: tensor([-0.0052,  0.0295])\n",
      "\tparams: tensor([  5.3371, -17.1317])\n",
      "Epoch: 2717,Loss: 2.930270\n",
      "\tgrad: tensor([-0.0052,  0.0294])\n",
      "\tparams: tensor([  5.3372, -17.1320])\n",
      "Epoch: 2718,Loss: 2.930262\n",
      "\tgrad: tensor([-0.0052,  0.0294])\n",
      "\tparams: tensor([  5.3372, -17.1323])\n",
      "Epoch: 2719,Loss: 2.930254\n",
      "\tgrad: tensor([-0.0052,  0.0293])\n",
      "\tparams: tensor([  5.3373, -17.1326])\n",
      "Epoch: 2720,Loss: 2.930244\n",
      "\tgrad: tensor([-0.0052,  0.0293])\n",
      "\tparams: tensor([  5.3373, -17.1329])\n",
      "Epoch: 2721,Loss: 2.930235\n",
      "\tgrad: tensor([-0.0052,  0.0292])\n",
      "\tparams: tensor([  5.3374, -17.1332])\n",
      "Epoch: 2722,Loss: 2.930226\n",
      "\tgrad: tensor([-0.0052,  0.0292])\n",
      "\tparams: tensor([  5.3375, -17.1334])\n",
      "Epoch: 2723,Loss: 2.930218\n",
      "\tgrad: tensor([-0.0051,  0.0291])\n",
      "\tparams: tensor([  5.3375, -17.1337])\n",
      "Epoch: 2724,Loss: 2.930209\n",
      "\tgrad: tensor([-0.0051,  0.0291])\n",
      "\tparams: tensor([  5.3376, -17.1340])\n",
      "Epoch: 2725,Loss: 2.930201\n",
      "\tgrad: tensor([-0.0051,  0.0290])\n",
      "\tparams: tensor([  5.3376, -17.1343])\n",
      "Epoch: 2726,Loss: 2.930190\n",
      "\tgrad: tensor([-0.0051,  0.0290])\n",
      "\tparams: tensor([  5.3377, -17.1346])\n",
      "Epoch: 2727,Loss: 2.930183\n",
      "\tgrad: tensor([-0.0051,  0.0289])\n",
      "\tparams: tensor([  5.3377, -17.1349])\n",
      "Epoch: 2728,Loss: 2.930173\n",
      "\tgrad: tensor([-0.0051,  0.0289])\n",
      "\tparams: tensor([  5.3378, -17.1352])\n",
      "Epoch: 2729,Loss: 2.930166\n",
      "\tgrad: tensor([-0.0051,  0.0288])\n",
      "\tparams: tensor([  5.3378, -17.1355])\n",
      "Epoch: 2730,Loss: 2.930156\n",
      "\tgrad: tensor([-0.0051,  0.0288])\n",
      "\tparams: tensor([  5.3379, -17.1358])\n",
      "Epoch: 2731,Loss: 2.930149\n",
      "\tgrad: tensor([-0.0051,  0.0287])\n",
      "\tparams: tensor([  5.3379, -17.1360])\n",
      "Epoch: 2732,Loss: 2.930139\n",
      "\tgrad: tensor([-0.0051,  0.0287])\n",
      "\tparams: tensor([  5.3380, -17.1363])\n",
      "Epoch: 2733,Loss: 2.930131\n",
      "\tgrad: tensor([-0.0050,  0.0286])\n",
      "\tparams: tensor([  5.3380, -17.1366])\n",
      "Epoch: 2734,Loss: 2.930123\n",
      "\tgrad: tensor([-0.0050,  0.0286])\n",
      "\tparams: tensor([  5.3381, -17.1369])\n",
      "Epoch: 2735,Loss: 2.930113\n",
      "\tgrad: tensor([-0.0050,  0.0285])\n",
      "\tparams: tensor([  5.3381, -17.1372])\n",
      "Epoch: 2736,Loss: 2.930107\n",
      "\tgrad: tensor([-0.0051,  0.0285])\n",
      "\tparams: tensor([  5.3382, -17.1375])\n",
      "Epoch: 2737,Loss: 2.930099\n",
      "\tgrad: tensor([-0.0050,  0.0284])\n",
      "\tparams: tensor([  5.3382, -17.1378])\n",
      "Epoch: 2738,Loss: 2.930090\n",
      "\tgrad: tensor([-0.0050,  0.0284])\n",
      "\tparams: tensor([  5.3383, -17.1380])\n",
      "Epoch: 2739,Loss: 2.930081\n",
      "\tgrad: tensor([-0.0050,  0.0283])\n",
      "\tparams: tensor([  5.3383, -17.1383])\n",
      "Epoch: 2740,Loss: 2.930073\n",
      "\tgrad: tensor([-0.0050,  0.0283])\n",
      "\tparams: tensor([  5.3384, -17.1386])\n",
      "Epoch: 2741,Loss: 2.930064\n",
      "\tgrad: tensor([-0.0050,  0.0282])\n",
      "\tparams: tensor([  5.3384, -17.1389])\n",
      "Epoch: 2742,Loss: 2.930056\n",
      "\tgrad: tensor([-0.0050,  0.0282])\n",
      "\tparams: tensor([  5.3385, -17.1392])\n",
      "Epoch: 2743,Loss: 2.930048\n",
      "\tgrad: tensor([-0.0050,  0.0281])\n",
      "\tparams: tensor([  5.3385, -17.1395])\n",
      "Epoch: 2744,Loss: 2.930041\n",
      "\tgrad: tensor([-0.0050,  0.0281])\n",
      "\tparams: tensor([  5.3386, -17.1397])\n",
      "Epoch: 2745,Loss: 2.930032\n",
      "\tgrad: tensor([-0.0050,  0.0280])\n",
      "\tparams: tensor([  5.3386, -17.1400])\n",
      "Epoch: 2746,Loss: 2.930022\n",
      "\tgrad: tensor([-0.0050,  0.0280])\n",
      "\tparams: tensor([  5.3387, -17.1403])\n",
      "Epoch: 2747,Loss: 2.930016\n",
      "\tgrad: tensor([-0.0049,  0.0279])\n",
      "\tparams: tensor([  5.3387, -17.1406])\n",
      "Epoch: 2748,Loss: 2.930008\n",
      "\tgrad: tensor([-0.0049,  0.0279])\n",
      "\tparams: tensor([  5.3388, -17.1409])\n",
      "Epoch: 2749,Loss: 2.930000\n",
      "\tgrad: tensor([-0.0049,  0.0279])\n",
      "\tparams: tensor([  5.3388, -17.1411])\n",
      "Epoch: 2750,Loss: 2.929992\n",
      "\tgrad: tensor([-0.0049,  0.0278])\n",
      "\tparams: tensor([  5.3389, -17.1414])\n",
      "Epoch: 2751,Loss: 2.929983\n",
      "\tgrad: tensor([-0.0049,  0.0278])\n",
      "\tparams: tensor([  5.3389, -17.1417])\n",
      "Epoch: 2752,Loss: 2.929975\n",
      "\tgrad: tensor([-0.0049,  0.0277])\n",
      "\tparams: tensor([  5.3390, -17.1420])\n",
      "Epoch: 2753,Loss: 2.929968\n",
      "\tgrad: tensor([-0.0049,  0.0277])\n",
      "\tparams: tensor([  5.3390, -17.1422])\n",
      "Epoch: 2754,Loss: 2.929960\n",
      "\tgrad: tensor([-0.0049,  0.0276])\n",
      "\tparams: tensor([  5.3391, -17.1425])\n",
      "Epoch: 2755,Loss: 2.929953\n",
      "\tgrad: tensor([-0.0049,  0.0276])\n",
      "\tparams: tensor([  5.3391, -17.1428])\n",
      "Epoch: 2756,Loss: 2.929945\n",
      "\tgrad: tensor([-0.0049,  0.0275])\n",
      "\tparams: tensor([  5.3392, -17.1431])\n",
      "Epoch: 2757,Loss: 2.929936\n",
      "\tgrad: tensor([-0.0049,  0.0275])\n",
      "\tparams: tensor([  5.3392, -17.1433])\n",
      "Epoch: 2758,Loss: 2.929929\n",
      "\tgrad: tensor([-0.0049,  0.0274])\n",
      "\tparams: tensor([  5.3392, -17.1436])\n",
      "Epoch: 2759,Loss: 2.929921\n",
      "\tgrad: tensor([-0.0048,  0.0274])\n",
      "\tparams: tensor([  5.3393, -17.1439])\n",
      "Epoch: 2760,Loss: 2.929914\n",
      "\tgrad: tensor([-0.0049,  0.0273])\n",
      "\tparams: tensor([  5.3393, -17.1442])\n",
      "Epoch: 2761,Loss: 2.929905\n",
      "\tgrad: tensor([-0.0048,  0.0273])\n",
      "\tparams: tensor([  5.3394, -17.1444])\n",
      "Epoch: 2762,Loss: 2.929896\n",
      "\tgrad: tensor([-0.0048,  0.0272])\n",
      "\tparams: tensor([  5.3394, -17.1447])\n",
      "Epoch: 2763,Loss: 2.929891\n",
      "\tgrad: tensor([-0.0048,  0.0272])\n",
      "\tparams: tensor([  5.3395, -17.1450])\n",
      "Epoch: 2764,Loss: 2.929882\n",
      "\tgrad: tensor([-0.0048,  0.0271])\n",
      "\tparams: tensor([  5.3395, -17.1453])\n",
      "Epoch: 2765,Loss: 2.929875\n",
      "\tgrad: tensor([-0.0048,  0.0271])\n",
      "\tparams: tensor([  5.3396, -17.1455])\n",
      "Epoch: 2766,Loss: 2.929868\n",
      "\tgrad: tensor([-0.0048,  0.0271])\n",
      "\tparams: tensor([  5.3396, -17.1458])\n",
      "Epoch: 2767,Loss: 2.929859\n",
      "\tgrad: tensor([-0.0048,  0.0270])\n",
      "\tparams: tensor([  5.3397, -17.1461])\n",
      "Epoch: 2768,Loss: 2.929852\n",
      "\tgrad: tensor([-0.0048,  0.0270])\n",
      "\tparams: tensor([  5.3397, -17.1463])\n",
      "Epoch: 2769,Loss: 2.929845\n",
      "\tgrad: tensor([-0.0048,  0.0269])\n",
      "\tparams: tensor([  5.3398, -17.1466])\n",
      "Epoch: 2770,Loss: 2.929838\n",
      "\tgrad: tensor([-0.0047,  0.0269])\n",
      "\tparams: tensor([  5.3398, -17.1469])\n",
      "Epoch: 2771,Loss: 2.929830\n",
      "\tgrad: tensor([-0.0047,  0.0268])\n",
      "\tparams: tensor([  5.3399, -17.1471])\n",
      "Epoch: 2772,Loss: 2.929822\n",
      "\tgrad: tensor([-0.0047,  0.0268])\n",
      "\tparams: tensor([  5.3399, -17.1474])\n",
      "Epoch: 2773,Loss: 2.929816\n",
      "\tgrad: tensor([-0.0047,  0.0267])\n",
      "\tparams: tensor([  5.3400, -17.1477])\n",
      "Epoch: 2774,Loss: 2.929807\n",
      "\tgrad: tensor([-0.0047,  0.0267])\n",
      "\tparams: tensor([  5.3400, -17.1479])\n",
      "Epoch: 2775,Loss: 2.929800\n",
      "\tgrad: tensor([-0.0047,  0.0266])\n",
      "\tparams: tensor([  5.3401, -17.1482])\n",
      "Epoch: 2776,Loss: 2.929794\n",
      "\tgrad: tensor([-0.0047,  0.0266])\n",
      "\tparams: tensor([  5.3401, -17.1485])\n",
      "Epoch: 2777,Loss: 2.929786\n",
      "\tgrad: tensor([-0.0047,  0.0266])\n",
      "\tparams: tensor([  5.3402, -17.1487])\n",
      "Epoch: 2778,Loss: 2.929778\n",
      "\tgrad: tensor([-0.0047,  0.0265])\n",
      "\tparams: tensor([  5.3402, -17.1490])\n",
      "Epoch: 2779,Loss: 2.929771\n",
      "\tgrad: tensor([-0.0047,  0.0265])\n",
      "\tparams: tensor([  5.3402, -17.1493])\n",
      "Epoch: 2780,Loss: 2.929765\n",
      "\tgrad: tensor([-0.0047,  0.0264])\n",
      "\tparams: tensor([  5.3403, -17.1495])\n",
      "Epoch: 2781,Loss: 2.929757\n",
      "\tgrad: tensor([-0.0047,  0.0264])\n",
      "\tparams: tensor([  5.3403, -17.1498])\n",
      "Epoch: 2782,Loss: 2.929750\n",
      "\tgrad: tensor([-0.0046,  0.0263])\n",
      "\tparams: tensor([  5.3404, -17.1501])\n",
      "Epoch: 2783,Loss: 2.929743\n",
      "\tgrad: tensor([-0.0046,  0.0263])\n",
      "\tparams: tensor([  5.3404, -17.1503])\n",
      "Epoch: 2784,Loss: 2.929735\n",
      "\tgrad: tensor([-0.0046,  0.0262])\n",
      "\tparams: tensor([  5.3405, -17.1506])\n",
      "Epoch: 2785,Loss: 2.929729\n",
      "\tgrad: tensor([-0.0047,  0.0262])\n",
      "\tparams: tensor([  5.3405, -17.1508])\n",
      "Epoch: 2786,Loss: 2.929722\n",
      "\tgrad: tensor([-0.0046,  0.0262])\n",
      "\tparams: tensor([  5.3406, -17.1511])\n",
      "Epoch: 2787,Loss: 2.929714\n",
      "\tgrad: tensor([-0.0046,  0.0261])\n",
      "\tparams: tensor([  5.3406, -17.1514])\n",
      "Epoch: 2788,Loss: 2.929707\n",
      "\tgrad: tensor([-0.0046,  0.0261])\n",
      "\tparams: tensor([  5.3407, -17.1516])\n",
      "Epoch: 2789,Loss: 2.929701\n",
      "\tgrad: tensor([-0.0046,  0.0260])\n",
      "\tparams: tensor([  5.3407, -17.1519])\n",
      "Epoch: 2790,Loss: 2.929692\n",
      "\tgrad: tensor([-0.0046,  0.0260])\n",
      "\tparams: tensor([  5.3408, -17.1522])\n",
      "Epoch: 2791,Loss: 2.929685\n",
      "\tgrad: tensor([-0.0046,  0.0259])\n",
      "\tparams: tensor([  5.3408, -17.1524])\n",
      "Epoch: 2792,Loss: 2.929681\n",
      "\tgrad: tensor([-0.0046,  0.0259])\n",
      "\tparams: tensor([  5.3408, -17.1527])\n",
      "Epoch: 2793,Loss: 2.929672\n",
      "\tgrad: tensor([-0.0046,  0.0258])\n",
      "\tparams: tensor([  5.3409, -17.1529])\n",
      "Epoch: 2794,Loss: 2.929666\n",
      "\tgrad: tensor([-0.0046,  0.0258])\n",
      "\tparams: tensor([  5.3409, -17.1532])\n",
      "Epoch: 2795,Loss: 2.929659\n",
      "\tgrad: tensor([-0.0045,  0.0258])\n",
      "\tparams: tensor([  5.3410, -17.1534])\n",
      "Epoch: 2796,Loss: 2.929653\n",
      "\tgrad: tensor([-0.0045,  0.0257])\n",
      "\tparams: tensor([  5.3410, -17.1537])\n",
      "Epoch: 2797,Loss: 2.929646\n",
      "\tgrad: tensor([-0.0045,  0.0257])\n",
      "\tparams: tensor([  5.3411, -17.1540])\n",
      "Epoch: 2798,Loss: 2.929638\n",
      "\tgrad: tensor([-0.0045,  0.0256])\n",
      "\tparams: tensor([  5.3411, -17.1542])\n",
      "Epoch: 2799,Loss: 2.929632\n",
      "\tgrad: tensor([-0.0045,  0.0256])\n",
      "\tparams: tensor([  5.3412, -17.1545])\n",
      "Epoch: 2800,Loss: 2.929626\n",
      "\tgrad: tensor([-0.0045,  0.0255])\n",
      "\tparams: tensor([  5.3412, -17.1547])\n",
      "Epoch: 2801,Loss: 2.929620\n",
      "\tgrad: tensor([-0.0045,  0.0255])\n",
      "\tparams: tensor([  5.3413, -17.1550])\n",
      "Epoch: 2802,Loss: 2.929611\n",
      "\tgrad: tensor([-0.0045,  0.0254])\n",
      "\tparams: tensor([  5.3413, -17.1552])\n",
      "Epoch: 2803,Loss: 2.929605\n",
      "\tgrad: tensor([-0.0045,  0.0254])\n",
      "\tparams: tensor([  5.3413, -17.1555])\n",
      "Epoch: 2804,Loss: 2.929600\n",
      "\tgrad: tensor([-0.0045,  0.0254])\n",
      "\tparams: tensor([  5.3414, -17.1557])\n",
      "Epoch: 2805,Loss: 2.929592\n",
      "\tgrad: tensor([-0.0045,  0.0253])\n",
      "\tparams: tensor([  5.3414, -17.1560])\n",
      "Epoch: 2806,Loss: 2.929586\n",
      "\tgrad: tensor([-0.0045,  0.0253])\n",
      "\tparams: tensor([  5.3415, -17.1562])\n",
      "Epoch: 2807,Loss: 2.929579\n",
      "\tgrad: tensor([-0.0045,  0.0252])\n",
      "\tparams: tensor([  5.3415, -17.1565])\n",
      "Epoch: 2808,Loss: 2.929572\n",
      "\tgrad: tensor([-0.0044,  0.0252])\n",
      "\tparams: tensor([  5.3416, -17.1568])\n",
      "Epoch: 2809,Loss: 2.929566\n",
      "\tgrad: tensor([-0.0044,  0.0251])\n",
      "\tparams: tensor([  5.3416, -17.1570])\n",
      "Epoch: 2810,Loss: 2.929559\n",
      "\tgrad: tensor([-0.0044,  0.0251])\n",
      "\tparams: tensor([  5.3417, -17.1573])\n",
      "Epoch: 2811,Loss: 2.929551\n",
      "\tgrad: tensor([-0.0044,  0.0251])\n",
      "\tparams: tensor([  5.3417, -17.1575])\n",
      "Epoch: 2812,Loss: 2.929545\n",
      "\tgrad: tensor([-0.0044,  0.0250])\n",
      "\tparams: tensor([  5.3417, -17.1578])\n",
      "Epoch: 2813,Loss: 2.929540\n",
      "\tgrad: tensor([-0.0044,  0.0250])\n",
      "\tparams: tensor([  5.3418, -17.1580])\n",
      "Epoch: 2814,Loss: 2.929533\n",
      "\tgrad: tensor([-0.0044,  0.0249])\n",
      "\tparams: tensor([  5.3418, -17.1583])\n",
      "Epoch: 2815,Loss: 2.929528\n",
      "\tgrad: tensor([-0.0044,  0.0249])\n",
      "\tparams: tensor([  5.3419, -17.1585])\n",
      "Epoch: 2816,Loss: 2.929521\n",
      "\tgrad: tensor([-0.0044,  0.0249])\n",
      "\tparams: tensor([  5.3419, -17.1588])\n",
      "Epoch: 2817,Loss: 2.929513\n",
      "\tgrad: tensor([-0.0044,  0.0248])\n",
      "\tparams: tensor([  5.3420, -17.1590])\n",
      "Epoch: 2818,Loss: 2.929507\n",
      "\tgrad: tensor([-0.0043,  0.0248])\n",
      "\tparams: tensor([  5.3420, -17.1592])\n",
      "Epoch: 2819,Loss: 2.929501\n",
      "\tgrad: tensor([-0.0044,  0.0247])\n",
      "\tparams: tensor([  5.3421, -17.1595])\n",
      "Epoch: 2820,Loss: 2.929496\n",
      "\tgrad: tensor([-0.0044,  0.0247])\n",
      "\tparams: tensor([  5.3421, -17.1597])\n",
      "Epoch: 2821,Loss: 2.929489\n",
      "\tgrad: tensor([-0.0044,  0.0246])\n",
      "\tparams: tensor([  5.3421, -17.1600])\n",
      "Epoch: 2822,Loss: 2.929482\n",
      "\tgrad: tensor([-0.0043,  0.0246])\n",
      "\tparams: tensor([  5.3422, -17.1602])\n",
      "Epoch: 2823,Loss: 2.929476\n",
      "\tgrad: tensor([-0.0043,  0.0246])\n",
      "\tparams: tensor([  5.3422, -17.1605])\n",
      "Epoch: 2824,Loss: 2.929471\n",
      "\tgrad: tensor([-0.0043,  0.0245])\n",
      "\tparams: tensor([  5.3423, -17.1607])\n",
      "Epoch: 2825,Loss: 2.929463\n",
      "\tgrad: tensor([-0.0043,  0.0245])\n",
      "\tparams: tensor([  5.3423, -17.1610])\n",
      "Epoch: 2826,Loss: 2.929458\n",
      "\tgrad: tensor([-0.0043,  0.0244])\n",
      "\tparams: tensor([  5.3424, -17.1612])\n",
      "Epoch: 2827,Loss: 2.929452\n",
      "\tgrad: tensor([-0.0043,  0.0244])\n",
      "\tparams: tensor([  5.3424, -17.1615])\n",
      "Epoch: 2828,Loss: 2.929445\n",
      "\tgrad: tensor([-0.0043,  0.0243])\n",
      "\tparams: tensor([  5.3424, -17.1617])\n",
      "Epoch: 2829,Loss: 2.929439\n",
      "\tgrad: tensor([-0.0043,  0.0243])\n",
      "\tparams: tensor([  5.3425, -17.1619])\n",
      "Epoch: 2830,Loss: 2.929433\n",
      "\tgrad: tensor([-0.0043,  0.0243])\n",
      "\tparams: tensor([  5.3425, -17.1622])\n",
      "Epoch: 2831,Loss: 2.929427\n",
      "\tgrad: tensor([-0.0043,  0.0242])\n",
      "\tparams: tensor([  5.3426, -17.1624])\n",
      "Epoch: 2832,Loss: 2.929421\n",
      "\tgrad: tensor([-0.0043,  0.0242])\n",
      "\tparams: tensor([  5.3426, -17.1627])\n",
      "Epoch: 2833,Loss: 2.929415\n",
      "\tgrad: tensor([-0.0043,  0.0241])\n",
      "\tparams: tensor([  5.3427, -17.1629])\n",
      "Epoch: 2834,Loss: 2.929409\n",
      "\tgrad: tensor([-0.0043,  0.0241])\n",
      "\tparams: tensor([  5.3427, -17.1632])\n",
      "Epoch: 2835,Loss: 2.929404\n",
      "\tgrad: tensor([-0.0043,  0.0241])\n",
      "\tparams: tensor([  5.3427, -17.1634])\n",
      "Epoch: 2836,Loss: 2.929396\n",
      "\tgrad: tensor([-0.0042,  0.0240])\n",
      "\tparams: tensor([  5.3428, -17.1636])\n",
      "Epoch: 2837,Loss: 2.929391\n",
      "\tgrad: tensor([-0.0042,  0.0240])\n",
      "\tparams: tensor([  5.3428, -17.1639])\n",
      "Epoch: 2838,Loss: 2.929383\n",
      "\tgrad: tensor([-0.0042,  0.0239])\n",
      "\tparams: tensor([  5.3429, -17.1641])\n",
      "Epoch: 2839,Loss: 2.929380\n",
      "\tgrad: tensor([-0.0042,  0.0239])\n",
      "\tparams: tensor([  5.3429, -17.1644])\n",
      "Epoch: 2840,Loss: 2.929373\n",
      "\tgrad: tensor([-0.0042,  0.0239])\n",
      "\tparams: tensor([  5.3430, -17.1646])\n",
      "Epoch: 2841,Loss: 2.929368\n",
      "\tgrad: tensor([-0.0042,  0.0238])\n",
      "\tparams: tensor([  5.3430, -17.1648])\n",
      "Epoch: 2842,Loss: 2.929361\n",
      "\tgrad: tensor([-0.0042,  0.0238])\n",
      "\tparams: tensor([  5.3430, -17.1651])\n",
      "Epoch: 2843,Loss: 2.929356\n",
      "\tgrad: tensor([-0.0042,  0.0237])\n",
      "\tparams: tensor([  5.3431, -17.1653])\n",
      "Epoch: 2844,Loss: 2.929351\n",
      "\tgrad: tensor([-0.0042,  0.0237])\n",
      "\tparams: tensor([  5.3431, -17.1655])\n",
      "Epoch: 2845,Loss: 2.929344\n",
      "\tgrad: tensor([-0.0042,  0.0237])\n",
      "\tparams: tensor([  5.3432, -17.1658])\n",
      "Epoch: 2846,Loss: 2.929338\n",
      "\tgrad: tensor([-0.0042,  0.0236])\n",
      "\tparams: tensor([  5.3432, -17.1660])\n",
      "Epoch: 2847,Loss: 2.929332\n",
      "\tgrad: tensor([-0.0042,  0.0236])\n",
      "\tparams: tensor([  5.3432, -17.1662])\n",
      "Epoch: 2848,Loss: 2.929328\n",
      "\tgrad: tensor([-0.0042,  0.0235])\n",
      "\tparams: tensor([  5.3433, -17.1665])\n",
      "Epoch: 2849,Loss: 2.929321\n",
      "\tgrad: tensor([-0.0041,  0.0235])\n",
      "\tparams: tensor([  5.3433, -17.1667])\n",
      "Epoch: 2850,Loss: 2.929316\n",
      "\tgrad: tensor([-0.0041,  0.0235])\n",
      "\tparams: tensor([  5.3434, -17.1670])\n",
      "Epoch: 2851,Loss: 2.929309\n",
      "\tgrad: tensor([-0.0041,  0.0234])\n",
      "\tparams: tensor([  5.3434, -17.1672])\n",
      "Epoch: 2852,Loss: 2.929304\n",
      "\tgrad: tensor([-0.0041,  0.0234])\n",
      "\tparams: tensor([  5.3435, -17.1674])\n",
      "Epoch: 2853,Loss: 2.929300\n",
      "\tgrad: tensor([-0.0041,  0.0233])\n",
      "\tparams: tensor([  5.3435, -17.1677])\n",
      "Epoch: 2854,Loss: 2.929293\n",
      "\tgrad: tensor([-0.0041,  0.0233])\n",
      "\tparams: tensor([  5.3435, -17.1679])\n",
      "Epoch: 2855,Loss: 2.929288\n",
      "\tgrad: tensor([-0.0041,  0.0233])\n",
      "\tparams: tensor([  5.3436, -17.1681])\n",
      "Epoch: 2856,Loss: 2.929282\n",
      "\tgrad: tensor([-0.0041,  0.0232])\n",
      "\tparams: tensor([  5.3436, -17.1684])\n",
      "Epoch: 2857,Loss: 2.929277\n",
      "\tgrad: tensor([-0.0041,  0.0232])\n",
      "\tparams: tensor([  5.3437, -17.1686])\n",
      "Epoch: 2858,Loss: 2.929271\n",
      "\tgrad: tensor([-0.0041,  0.0231])\n",
      "\tparams: tensor([  5.3437, -17.1688])\n",
      "Epoch: 2859,Loss: 2.929266\n",
      "\tgrad: tensor([-0.0041,  0.0231])\n",
      "\tparams: tensor([  5.3437, -17.1690])\n",
      "Epoch: 2860,Loss: 2.929260\n",
      "\tgrad: tensor([-0.0041,  0.0231])\n",
      "\tparams: tensor([  5.3438, -17.1693])\n",
      "Epoch: 2861,Loss: 2.929255\n",
      "\tgrad: tensor([-0.0041,  0.0230])\n",
      "\tparams: tensor([  5.3438, -17.1695])\n",
      "Epoch: 2862,Loss: 2.929250\n",
      "\tgrad: tensor([-0.0041,  0.0230])\n",
      "\tparams: tensor([  5.3439, -17.1697])\n",
      "Epoch: 2863,Loss: 2.929244\n",
      "\tgrad: tensor([-0.0040,  0.0229])\n",
      "\tparams: tensor([  5.3439, -17.1700])\n",
      "Epoch: 2864,Loss: 2.929238\n",
      "\tgrad: tensor([-0.0040,  0.0229])\n",
      "\tparams: tensor([  5.3439, -17.1702])\n",
      "Epoch: 2865,Loss: 2.929234\n",
      "\tgrad: tensor([-0.0040,  0.0229])\n",
      "\tparams: tensor([  5.3440, -17.1704])\n",
      "Epoch: 2866,Loss: 2.929228\n",
      "\tgrad: tensor([-0.0040,  0.0228])\n",
      "\tparams: tensor([  5.3440, -17.1707])\n",
      "Epoch: 2867,Loss: 2.929222\n",
      "\tgrad: tensor([-0.0040,  0.0228])\n",
      "\tparams: tensor([  5.3441, -17.1709])\n",
      "Epoch: 2868,Loss: 2.929217\n",
      "\tgrad: tensor([-0.0040,  0.0227])\n",
      "\tparams: tensor([  5.3441, -17.1711])\n",
      "Epoch: 2869,Loss: 2.929211\n",
      "\tgrad: tensor([-0.0040,  0.0227])\n",
      "\tparams: tensor([  5.3441, -17.1713])\n",
      "Epoch: 2870,Loss: 2.929208\n",
      "\tgrad: tensor([-0.0040,  0.0227])\n",
      "\tparams: tensor([  5.3442, -17.1716])\n",
      "Epoch: 2871,Loss: 2.929201\n",
      "\tgrad: tensor([-0.0040,  0.0226])\n",
      "\tparams: tensor([  5.3442, -17.1718])\n",
      "Epoch: 2872,Loss: 2.929195\n",
      "\tgrad: tensor([-0.0040,  0.0226])\n",
      "\tparams: tensor([  5.3443, -17.1720])\n",
      "Epoch: 2873,Loss: 2.929191\n",
      "\tgrad: tensor([-0.0040,  0.0226])\n",
      "\tparams: tensor([  5.3443, -17.1722])\n",
      "Epoch: 2874,Loss: 2.929185\n",
      "\tgrad: tensor([-0.0040,  0.0225])\n",
      "\tparams: tensor([  5.3443, -17.1725])\n",
      "Epoch: 2875,Loss: 2.929180\n",
      "\tgrad: tensor([-0.0040,  0.0225])\n",
      "\tparams: tensor([  5.3444, -17.1727])\n",
      "Epoch: 2876,Loss: 2.929175\n",
      "\tgrad: tensor([-0.0040,  0.0224])\n",
      "\tparams: tensor([  5.3444, -17.1729])\n",
      "Epoch: 2877,Loss: 2.929170\n",
      "\tgrad: tensor([-0.0040,  0.0224])\n",
      "\tparams: tensor([  5.3445, -17.1731])\n",
      "Epoch: 2878,Loss: 2.929165\n",
      "\tgrad: tensor([-0.0040,  0.0224])\n",
      "\tparams: tensor([  5.3445, -17.1734])\n",
      "Epoch: 2879,Loss: 2.929160\n",
      "\tgrad: tensor([-0.0039,  0.0223])\n",
      "\tparams: tensor([  5.3445, -17.1736])\n",
      "Epoch: 2880,Loss: 2.929155\n",
      "\tgrad: tensor([-0.0039,  0.0223])\n",
      "\tparams: tensor([  5.3446, -17.1738])\n",
      "Epoch: 2881,Loss: 2.929149\n",
      "\tgrad: tensor([-0.0039,  0.0223])\n",
      "\tparams: tensor([  5.3446, -17.1740])\n",
      "Epoch: 2882,Loss: 2.929143\n",
      "\tgrad: tensor([-0.0039,  0.0222])\n",
      "\tparams: tensor([  5.3447, -17.1742])\n",
      "Epoch: 2883,Loss: 2.929139\n",
      "\tgrad: tensor([-0.0039,  0.0222])\n",
      "\tparams: tensor([  5.3447, -17.1745])\n",
      "Epoch: 2884,Loss: 2.929133\n",
      "\tgrad: tensor([-0.0039,  0.0221])\n",
      "\tparams: tensor([  5.3447, -17.1747])\n",
      "Epoch: 2885,Loss: 2.929128\n",
      "\tgrad: tensor([-0.0039,  0.0221])\n",
      "\tparams: tensor([  5.3448, -17.1749])\n",
      "Epoch: 2886,Loss: 2.929122\n",
      "\tgrad: tensor([-0.0039,  0.0221])\n",
      "\tparams: tensor([  5.3448, -17.1751])\n",
      "Epoch: 2887,Loss: 2.929119\n",
      "\tgrad: tensor([-0.0039,  0.0220])\n",
      "\tparams: tensor([  5.3449, -17.1754])\n",
      "Epoch: 2888,Loss: 2.929113\n",
      "\tgrad: tensor([-0.0039,  0.0220])\n",
      "\tparams: tensor([  5.3449, -17.1756])\n",
      "Epoch: 2889,Loss: 2.929108\n",
      "\tgrad: tensor([-0.0039,  0.0220])\n",
      "\tparams: tensor([  5.3449, -17.1758])\n",
      "Epoch: 2890,Loss: 2.929104\n",
      "\tgrad: tensor([-0.0039,  0.0219])\n",
      "\tparams: tensor([  5.3450, -17.1760])\n",
      "Epoch: 2891,Loss: 2.929099\n",
      "\tgrad: tensor([-0.0039,  0.0219])\n",
      "\tparams: tensor([  5.3450, -17.1762])\n",
      "Epoch: 2892,Loss: 2.929093\n",
      "\tgrad: tensor([-0.0039,  0.0218])\n",
      "\tparams: tensor([  5.3450, -17.1764])\n",
      "Epoch: 2893,Loss: 2.929088\n",
      "\tgrad: tensor([-0.0039,  0.0218])\n",
      "\tparams: tensor([  5.3451, -17.1767])\n",
      "Epoch: 2894,Loss: 2.929083\n",
      "\tgrad: tensor([-0.0038,  0.0218])\n",
      "\tparams: tensor([  5.3451, -17.1769])\n",
      "Epoch: 2895,Loss: 2.929079\n",
      "\tgrad: tensor([-0.0038,  0.0217])\n",
      "\tparams: tensor([  5.3452, -17.1771])\n",
      "Epoch: 2896,Loss: 2.929074\n",
      "\tgrad: tensor([-0.0038,  0.0217])\n",
      "\tparams: tensor([  5.3452, -17.1773])\n",
      "Epoch: 2897,Loss: 2.929069\n",
      "\tgrad: tensor([-0.0038,  0.0217])\n",
      "\tparams: tensor([  5.3452, -17.1775])\n",
      "Epoch: 2898,Loss: 2.929065\n",
      "\tgrad: tensor([-0.0038,  0.0216])\n",
      "\tparams: tensor([  5.3453, -17.1777])\n",
      "Epoch: 2899,Loss: 2.929058\n",
      "\tgrad: tensor([-0.0038,  0.0216])\n",
      "\tparams: tensor([  5.3453, -17.1780])\n",
      "Epoch: 2900,Loss: 2.929054\n",
      "\tgrad: tensor([-0.0038,  0.0215])\n",
      "\tparams: tensor([  5.3454, -17.1782])\n",
      "Epoch: 2901,Loss: 2.929050\n",
      "\tgrad: tensor([-0.0038,  0.0215])\n",
      "\tparams: tensor([  5.3454, -17.1784])\n",
      "Epoch: 2902,Loss: 2.929044\n",
      "\tgrad: tensor([-0.0038,  0.0215])\n",
      "\tparams: tensor([  5.3454, -17.1786])\n",
      "Epoch: 2903,Loss: 2.929041\n",
      "\tgrad: tensor([-0.0038,  0.0214])\n",
      "\tparams: tensor([  5.3455, -17.1788])\n",
      "Epoch: 2904,Loss: 2.929036\n",
      "\tgrad: tensor([-0.0038,  0.0214])\n",
      "\tparams: tensor([  5.3455, -17.1790])\n",
      "Epoch: 2905,Loss: 2.929031\n",
      "\tgrad: tensor([-0.0038,  0.0214])\n",
      "\tparams: tensor([  5.3455, -17.1793])\n",
      "Epoch: 2906,Loss: 2.929025\n",
      "\tgrad: tensor([-0.0038,  0.0213])\n",
      "\tparams: tensor([  5.3456, -17.1795])\n",
      "Epoch: 2907,Loss: 2.929021\n",
      "\tgrad: tensor([-0.0038,  0.0213])\n",
      "\tparams: tensor([  5.3456, -17.1797])\n",
      "Epoch: 2908,Loss: 2.929017\n",
      "\tgrad: tensor([-0.0037,  0.0213])\n",
      "\tparams: tensor([  5.3457, -17.1799])\n",
      "Epoch: 2909,Loss: 2.929012\n",
      "\tgrad: tensor([-0.0037,  0.0212])\n",
      "\tparams: tensor([  5.3457, -17.1801])\n",
      "Epoch: 2910,Loss: 2.929007\n",
      "\tgrad: tensor([-0.0037,  0.0212])\n",
      "\tparams: tensor([  5.3457, -17.1803])\n",
      "Epoch: 2911,Loss: 2.929003\n",
      "\tgrad: tensor([-0.0037,  0.0211])\n",
      "\tparams: tensor([  5.3458, -17.1805])\n",
      "Epoch: 2912,Loss: 2.928999\n",
      "\tgrad: tensor([-0.0037,  0.0211])\n",
      "\tparams: tensor([  5.3458, -17.1807])\n",
      "Epoch: 2913,Loss: 2.928993\n",
      "\tgrad: tensor([-0.0037,  0.0211])\n",
      "\tparams: tensor([  5.3458, -17.1809])\n",
      "Epoch: 2914,Loss: 2.928989\n",
      "\tgrad: tensor([-0.0037,  0.0210])\n",
      "\tparams: tensor([  5.3459, -17.1812])\n",
      "Epoch: 2915,Loss: 2.928985\n",
      "\tgrad: tensor([-0.0037,  0.0210])\n",
      "\tparams: tensor([  5.3459, -17.1814])\n",
      "Epoch: 2916,Loss: 2.928980\n",
      "\tgrad: tensor([-0.0037,  0.0210])\n",
      "\tparams: tensor([  5.3460, -17.1816])\n",
      "Epoch: 2917,Loss: 2.928976\n",
      "\tgrad: tensor([-0.0037,  0.0209])\n",
      "\tparams: tensor([  5.3460, -17.1818])\n",
      "Epoch: 2918,Loss: 2.928971\n",
      "\tgrad: tensor([-0.0037,  0.0209])\n",
      "\tparams: tensor([  5.3460, -17.1820])\n",
      "Epoch: 2919,Loss: 2.928967\n",
      "\tgrad: tensor([-0.0037,  0.0209])\n",
      "\tparams: tensor([  5.3461, -17.1822])\n",
      "Epoch: 2920,Loss: 2.928962\n",
      "\tgrad: tensor([-0.0037,  0.0208])\n",
      "\tparams: tensor([  5.3461, -17.1824])\n",
      "Epoch: 2921,Loss: 2.928958\n",
      "\tgrad: tensor([-0.0037,  0.0208])\n",
      "\tparams: tensor([  5.3461, -17.1826])\n",
      "Epoch: 2922,Loss: 2.928953\n",
      "\tgrad: tensor([-0.0037,  0.0208])\n",
      "\tparams: tensor([  5.3462, -17.1828])\n",
      "Epoch: 2923,Loss: 2.928947\n",
      "\tgrad: tensor([-0.0036,  0.0207])\n",
      "\tparams: tensor([  5.3462, -17.1830])\n",
      "Epoch: 2924,Loss: 2.928943\n",
      "\tgrad: tensor([-0.0037,  0.0207])\n",
      "\tparams: tensor([  5.3462, -17.1832])\n",
      "Epoch: 2925,Loss: 2.928940\n",
      "\tgrad: tensor([-0.0036,  0.0206])\n",
      "\tparams: tensor([  5.3463, -17.1834])\n",
      "Epoch: 2926,Loss: 2.928935\n",
      "\tgrad: tensor([-0.0036,  0.0206])\n",
      "\tparams: tensor([  5.3463, -17.1837])\n",
      "Epoch: 2927,Loss: 2.928932\n",
      "\tgrad: tensor([-0.0036,  0.0206])\n",
      "\tparams: tensor([  5.3464, -17.1839])\n",
      "Epoch: 2928,Loss: 2.928926\n",
      "\tgrad: tensor([-0.0036,  0.0205])\n",
      "\tparams: tensor([  5.3464, -17.1841])\n",
      "Epoch: 2929,Loss: 2.928923\n",
      "\tgrad: tensor([-0.0036,  0.0205])\n",
      "\tparams: tensor([  5.3464, -17.1843])\n",
      "Epoch: 2930,Loss: 2.928919\n",
      "\tgrad: tensor([-0.0036,  0.0205])\n",
      "\tparams: tensor([  5.3465, -17.1845])\n",
      "Epoch: 2931,Loss: 2.928913\n",
      "\tgrad: tensor([-0.0036,  0.0204])\n",
      "\tparams: tensor([  5.3465, -17.1847])\n",
      "Epoch: 2932,Loss: 2.928909\n",
      "\tgrad: tensor([-0.0036,  0.0204])\n",
      "\tparams: tensor([  5.3465, -17.1849])\n",
      "Epoch: 2933,Loss: 2.928904\n",
      "\tgrad: tensor([-0.0036,  0.0204])\n",
      "\tparams: tensor([  5.3466, -17.1851])\n",
      "Epoch: 2934,Loss: 2.928902\n",
      "\tgrad: tensor([-0.0036,  0.0203])\n",
      "\tparams: tensor([  5.3466, -17.1853])\n",
      "Epoch: 2935,Loss: 2.928897\n",
      "\tgrad: tensor([-0.0036,  0.0203])\n",
      "\tparams: tensor([  5.3466, -17.1855])\n",
      "Epoch: 2936,Loss: 2.928893\n",
      "\tgrad: tensor([-0.0036,  0.0203])\n",
      "\tparams: tensor([  5.3467, -17.1857])\n",
      "Epoch: 2937,Loss: 2.928887\n",
      "\tgrad: tensor([-0.0036,  0.0202])\n",
      "\tparams: tensor([  5.3467, -17.1859])\n",
      "Epoch: 2938,Loss: 2.928883\n",
      "\tgrad: tensor([-0.0035,  0.0202])\n",
      "\tparams: tensor([  5.3468, -17.1861])\n",
      "Epoch: 2939,Loss: 2.928880\n",
      "\tgrad: tensor([-0.0036,  0.0202])\n",
      "\tparams: tensor([  5.3468, -17.1863])\n",
      "Epoch: 2940,Loss: 2.928878\n",
      "\tgrad: tensor([-0.0036,  0.0201])\n",
      "\tparams: tensor([  5.3468, -17.1865])\n",
      "Epoch: 2941,Loss: 2.928871\n",
      "\tgrad: tensor([-0.0035,  0.0201])\n",
      "\tparams: tensor([  5.3469, -17.1867])\n",
      "Epoch: 2942,Loss: 2.928867\n",
      "\tgrad: tensor([-0.0035,  0.0201])\n",
      "\tparams: tensor([  5.3469, -17.1869])\n",
      "Epoch: 2943,Loss: 2.928864\n",
      "\tgrad: tensor([-0.0035,  0.0200])\n",
      "\tparams: tensor([  5.3469, -17.1871])\n",
      "Epoch: 2944,Loss: 2.928860\n",
      "\tgrad: tensor([-0.0035,  0.0200])\n",
      "\tparams: tensor([  5.3470, -17.1873])\n",
      "Epoch: 2945,Loss: 2.928855\n",
      "\tgrad: tensor([-0.0035,  0.0200])\n",
      "\tparams: tensor([  5.3470, -17.1875])\n",
      "Epoch: 2946,Loss: 2.928850\n",
      "\tgrad: tensor([-0.0035,  0.0199])\n",
      "\tparams: tensor([  5.3470, -17.1877])\n",
      "Epoch: 2947,Loss: 2.928845\n",
      "\tgrad: tensor([-0.0035,  0.0199])\n",
      "\tparams: tensor([  5.3471, -17.1879])\n",
      "Epoch: 2948,Loss: 2.928843\n",
      "\tgrad: tensor([-0.0035,  0.0199])\n",
      "\tparams: tensor([  5.3471, -17.1881])\n",
      "Epoch: 2949,Loss: 2.928838\n",
      "\tgrad: tensor([-0.0035,  0.0198])\n",
      "\tparams: tensor([  5.3471, -17.1883])\n",
      "Epoch: 2950,Loss: 2.928833\n",
      "\tgrad: tensor([-0.0035,  0.0198])\n",
      "\tparams: tensor([  5.3472, -17.1885])\n",
      "Epoch: 2951,Loss: 2.928830\n",
      "\tgrad: tensor([-0.0035,  0.0198])\n",
      "\tparams: tensor([  5.3472, -17.1887])\n",
      "Epoch: 2952,Loss: 2.928826\n",
      "\tgrad: tensor([-0.0035,  0.0197])\n",
      "\tparams: tensor([  5.3472, -17.1889])\n",
      "Epoch: 2953,Loss: 2.928823\n",
      "\tgrad: tensor([-0.0035,  0.0197])\n",
      "\tparams: tensor([  5.3473, -17.1891])\n",
      "Epoch: 2954,Loss: 2.928818\n",
      "\tgrad: tensor([-0.0035,  0.0197])\n",
      "\tparams: tensor([  5.3473, -17.1893])\n",
      "Epoch: 2955,Loss: 2.928816\n",
      "\tgrad: tensor([-0.0035,  0.0196])\n",
      "\tparams: tensor([  5.3474, -17.1895])\n",
      "Epoch: 2956,Loss: 2.928811\n",
      "\tgrad: tensor([-0.0035,  0.0196])\n",
      "\tparams: tensor([  5.3474, -17.1897])\n",
      "Epoch: 2957,Loss: 2.928805\n",
      "\tgrad: tensor([-0.0034,  0.0196])\n",
      "\tparams: tensor([  5.3474, -17.1899])\n",
      "Epoch: 2958,Loss: 2.928802\n",
      "\tgrad: tensor([-0.0035,  0.0195])\n",
      "\tparams: tensor([  5.3475, -17.1901])\n",
      "Epoch: 2959,Loss: 2.928799\n",
      "\tgrad: tensor([-0.0034,  0.0195])\n",
      "\tparams: tensor([  5.3475, -17.1903])\n",
      "Epoch: 2960,Loss: 2.928795\n",
      "\tgrad: tensor([-0.0034,  0.0195])\n",
      "\tparams: tensor([  5.3475, -17.1905])\n",
      "Epoch: 2961,Loss: 2.928789\n",
      "\tgrad: tensor([-0.0034,  0.0194])\n",
      "\tparams: tensor([  5.3476, -17.1907])\n",
      "Epoch: 2962,Loss: 2.928789\n",
      "\tgrad: tensor([-0.0034,  0.0194])\n",
      "\tparams: tensor([  5.3476, -17.1908])\n",
      "Epoch: 2963,Loss: 2.928783\n",
      "\tgrad: tensor([-0.0034,  0.0194])\n",
      "\tparams: tensor([  5.3476, -17.1910])\n",
      "Epoch: 2964,Loss: 2.928779\n",
      "\tgrad: tensor([-0.0034,  0.0193])\n",
      "\tparams: tensor([  5.3477, -17.1912])\n",
      "Epoch: 2965,Loss: 2.928775\n",
      "\tgrad: tensor([-0.0034,  0.0193])\n",
      "\tparams: tensor([  5.3477, -17.1914])\n",
      "Epoch: 2966,Loss: 2.928771\n",
      "\tgrad: tensor([-0.0034,  0.0193])\n",
      "\tparams: tensor([  5.3477, -17.1916])\n",
      "Epoch: 2967,Loss: 2.928767\n",
      "\tgrad: tensor([-0.0034,  0.0192])\n",
      "\tparams: tensor([  5.3478, -17.1918])\n",
      "Epoch: 2968,Loss: 2.928765\n",
      "\tgrad: tensor([-0.0034,  0.0192])\n",
      "\tparams: tensor([  5.3478, -17.1920])\n",
      "Epoch: 2969,Loss: 2.928761\n",
      "\tgrad: tensor([-0.0034,  0.0192])\n",
      "\tparams: tensor([  5.3478, -17.1922])\n",
      "Epoch: 2970,Loss: 2.928758\n",
      "\tgrad: tensor([-0.0034,  0.0191])\n",
      "\tparams: tensor([  5.3479, -17.1924])\n",
      "Epoch: 2971,Loss: 2.928752\n",
      "\tgrad: tensor([-0.0034,  0.0191])\n",
      "\tparams: tensor([  5.3479, -17.1926])\n",
      "Epoch: 2972,Loss: 2.928750\n",
      "\tgrad: tensor([-0.0034,  0.0191])\n",
      "\tparams: tensor([  5.3479, -17.1928])\n",
      "Epoch: 2973,Loss: 2.928745\n",
      "\tgrad: tensor([-0.0034,  0.0190])\n",
      "\tparams: tensor([  5.3480, -17.1930])\n",
      "Epoch: 2974,Loss: 2.928741\n",
      "\tgrad: tensor([-0.0034,  0.0190])\n",
      "\tparams: tensor([  5.3480, -17.1931])\n",
      "Epoch: 2975,Loss: 2.928737\n",
      "\tgrad: tensor([-0.0034,  0.0190])\n",
      "\tparams: tensor([  5.3480, -17.1933])\n",
      "Epoch: 2976,Loss: 2.928735\n",
      "\tgrad: tensor([-0.0033,  0.0189])\n",
      "\tparams: tensor([  5.3481, -17.1935])\n",
      "Epoch: 2977,Loss: 2.928730\n",
      "\tgrad: tensor([-0.0033,  0.0189])\n",
      "\tparams: tensor([  5.3481, -17.1937])\n",
      "Epoch: 2978,Loss: 2.928727\n",
      "\tgrad: tensor([-0.0033,  0.0189])\n",
      "\tparams: tensor([  5.3481, -17.1939])\n",
      "Epoch: 2979,Loss: 2.928723\n",
      "\tgrad: tensor([-0.0033,  0.0188])\n",
      "\tparams: tensor([  5.3482, -17.1941])\n",
      "Epoch: 2980,Loss: 2.928719\n",
      "\tgrad: tensor([-0.0033,  0.0188])\n",
      "\tparams: tensor([  5.3482, -17.1943])\n",
      "Epoch: 2981,Loss: 2.928716\n",
      "\tgrad: tensor([-0.0033,  0.0188])\n",
      "\tparams: tensor([  5.3482, -17.1945])\n",
      "Epoch: 2982,Loss: 2.928712\n",
      "\tgrad: tensor([-0.0033,  0.0187])\n",
      "\tparams: tensor([  5.3483, -17.1947])\n",
      "Epoch: 2983,Loss: 2.928708\n",
      "\tgrad: tensor([-0.0033,  0.0187])\n",
      "\tparams: tensor([  5.3483, -17.1948])\n",
      "Epoch: 2984,Loss: 2.928705\n",
      "\tgrad: tensor([-0.0033,  0.0187])\n",
      "\tparams: tensor([  5.3483, -17.1950])\n",
      "Epoch: 2985,Loss: 2.928700\n",
      "\tgrad: tensor([-0.0033,  0.0186])\n",
      "\tparams: tensor([  5.3484, -17.1952])\n",
      "Epoch: 2986,Loss: 2.928698\n",
      "\tgrad: tensor([-0.0033,  0.0186])\n",
      "\tparams: tensor([  5.3484, -17.1954])\n",
      "Epoch: 2987,Loss: 2.928695\n",
      "\tgrad: tensor([-0.0033,  0.0186])\n",
      "\tparams: tensor([  5.3484, -17.1956])\n",
      "Epoch: 2988,Loss: 2.928690\n",
      "\tgrad: tensor([-0.0033,  0.0186])\n",
      "\tparams: tensor([  5.3485, -17.1958])\n",
      "Epoch: 2989,Loss: 2.928687\n",
      "\tgrad: tensor([-0.0033,  0.0185])\n",
      "\tparams: tensor([  5.3485, -17.1960])\n",
      "Epoch: 2990,Loss: 2.928684\n",
      "\tgrad: tensor([-0.0033,  0.0185])\n",
      "\tparams: tensor([  5.3485, -17.1961])\n",
      "Epoch: 2991,Loss: 2.928679\n",
      "\tgrad: tensor([-0.0032,  0.0185])\n",
      "\tparams: tensor([  5.3486, -17.1963])\n",
      "Epoch: 2992,Loss: 2.928677\n",
      "\tgrad: tensor([-0.0033,  0.0184])\n",
      "\tparams: tensor([  5.3486, -17.1965])\n",
      "Epoch: 2993,Loss: 2.928673\n",
      "\tgrad: tensor([-0.0033,  0.0184])\n",
      "\tparams: tensor([  5.3486, -17.1967])\n",
      "Epoch: 2994,Loss: 2.928669\n",
      "\tgrad: tensor([-0.0033,  0.0184])\n",
      "\tparams: tensor([  5.3487, -17.1969])\n",
      "Epoch: 2995,Loss: 2.928666\n",
      "\tgrad: tensor([-0.0032,  0.0183])\n",
      "\tparams: tensor([  5.3487, -17.1971])\n",
      "Epoch: 2996,Loss: 2.928662\n",
      "\tgrad: tensor([-0.0032,  0.0183])\n",
      "\tparams: tensor([  5.3487, -17.1972])\n",
      "Epoch: 2997,Loss: 2.928660\n",
      "\tgrad: tensor([-0.0032,  0.0183])\n",
      "\tparams: tensor([  5.3488, -17.1974])\n",
      "Epoch: 2998,Loss: 2.928656\n",
      "\tgrad: tensor([-0.0032,  0.0182])\n",
      "\tparams: tensor([  5.3488, -17.1976])\n",
      "Epoch: 2999,Loss: 2.928651\n",
      "\tgrad: tensor([-0.0032,  0.0182])\n",
      "\tparams: tensor([  5.3488, -17.1978])\n",
      "Epoch: 3000,Loss: 2.928648\n",
      "\tgrad: tensor([-0.0032,  0.0182])\n",
      "\tparams: tensor([  5.3489, -17.1980])\n",
      "Epoch: 3001,Loss: 2.928646\n",
      "\tgrad: tensor([-0.0032,  0.0181])\n",
      "\tparams: tensor([  5.3489, -17.1982])\n",
      "Epoch: 3002,Loss: 2.928643\n",
      "\tgrad: tensor([-0.0032,  0.0181])\n",
      "\tparams: tensor([  5.3489, -17.1983])\n",
      "Epoch: 3003,Loss: 2.928638\n",
      "\tgrad: tensor([-0.0032,  0.0181])\n",
      "\tparams: tensor([  5.3489, -17.1985])\n",
      "Epoch: 3004,Loss: 2.928635\n",
      "\tgrad: tensor([-0.0032,  0.0181])\n",
      "\tparams: tensor([  5.3490, -17.1987])\n",
      "Epoch: 3005,Loss: 2.928632\n",
      "\tgrad: tensor([-0.0032,  0.0180])\n",
      "\tparams: tensor([  5.3490, -17.1989])\n",
      "Epoch: 3006,Loss: 2.928629\n",
      "\tgrad: tensor([-0.0032,  0.0180])\n",
      "\tparams: tensor([  5.3490, -17.1991])\n",
      "Epoch: 3007,Loss: 2.928625\n",
      "\tgrad: tensor([-0.0032,  0.0180])\n",
      "\tparams: tensor([  5.3491, -17.1992])\n",
      "Epoch: 3008,Loss: 2.928621\n",
      "\tgrad: tensor([-0.0032,  0.0179])\n",
      "\tparams: tensor([  5.3491, -17.1994])\n",
      "Epoch: 3009,Loss: 2.928617\n",
      "\tgrad: tensor([-0.0032,  0.0179])\n",
      "\tparams: tensor([  5.3491, -17.1996])\n",
      "Epoch: 3010,Loss: 2.928616\n",
      "\tgrad: tensor([-0.0032,  0.0179])\n",
      "\tparams: tensor([  5.3492, -17.1998])\n",
      "Epoch: 3011,Loss: 2.928612\n",
      "\tgrad: tensor([-0.0032,  0.0178])\n",
      "\tparams: tensor([  5.3492, -17.2000])\n",
      "Epoch: 3012,Loss: 2.928608\n",
      "\tgrad: tensor([-0.0032,  0.0178])\n",
      "\tparams: tensor([  5.3492, -17.2001])\n",
      "Epoch: 3013,Loss: 2.928604\n",
      "\tgrad: tensor([-0.0031,  0.0178])\n",
      "\tparams: tensor([  5.3493, -17.2003])\n",
      "Epoch: 3014,Loss: 2.928601\n",
      "\tgrad: tensor([-0.0031,  0.0177])\n",
      "\tparams: tensor([  5.3493, -17.2005])\n",
      "Epoch: 3015,Loss: 2.928599\n",
      "\tgrad: tensor([-0.0031,  0.0177])\n",
      "\tparams: tensor([  5.3493, -17.2007])\n",
      "Epoch: 3016,Loss: 2.928596\n",
      "\tgrad: tensor([-0.0031,  0.0177])\n",
      "\tparams: tensor([  5.3494, -17.2008])\n",
      "Epoch: 3017,Loss: 2.928592\n",
      "\tgrad: tensor([-0.0031,  0.0177])\n",
      "\tparams: tensor([  5.3494, -17.2010])\n",
      "Epoch: 3018,Loss: 2.928588\n",
      "\tgrad: tensor([-0.0031,  0.0176])\n",
      "\tparams: tensor([  5.3494, -17.2012])\n",
      "Epoch: 3019,Loss: 2.928586\n",
      "\tgrad: tensor([-0.0031,  0.0176])\n",
      "\tparams: tensor([  5.3495, -17.2014])\n",
      "Epoch: 3020,Loss: 2.928583\n",
      "\tgrad: tensor([-0.0031,  0.0176])\n",
      "\tparams: tensor([  5.3495, -17.2015])\n",
      "Epoch: 3021,Loss: 2.928580\n",
      "\tgrad: tensor([-0.0031,  0.0175])\n",
      "\tparams: tensor([  5.3495, -17.2017])\n",
      "Epoch: 3022,Loss: 2.928576\n",
      "\tgrad: tensor([-0.0031,  0.0175])\n",
      "\tparams: tensor([  5.3495, -17.2019])\n",
      "Epoch: 3023,Loss: 2.928574\n",
      "\tgrad: tensor([-0.0031,  0.0175])\n",
      "\tparams: tensor([  5.3496, -17.2021])\n",
      "Epoch: 3024,Loss: 2.928570\n",
      "\tgrad: tensor([-0.0031,  0.0175])\n",
      "\tparams: tensor([  5.3496, -17.2022])\n",
      "Epoch: 3025,Loss: 2.928567\n",
      "\tgrad: tensor([-0.0031,  0.0174])\n",
      "\tparams: tensor([  5.3496, -17.2024])\n",
      "Epoch: 3026,Loss: 2.928564\n",
      "\tgrad: tensor([-0.0031,  0.0174])\n",
      "\tparams: tensor([  5.3497, -17.2026])\n",
      "Epoch: 3027,Loss: 2.928561\n",
      "\tgrad: tensor([-0.0030,  0.0174])\n",
      "\tparams: tensor([  5.3497, -17.2028])\n",
      "Epoch: 3028,Loss: 2.928557\n",
      "\tgrad: tensor([-0.0031,  0.0173])\n",
      "\tparams: tensor([  5.3497, -17.2029])\n",
      "Epoch: 3029,Loss: 2.928555\n",
      "\tgrad: tensor([-0.0031,  0.0173])\n",
      "\tparams: tensor([  5.3498, -17.2031])\n",
      "Epoch: 3030,Loss: 2.928551\n",
      "\tgrad: tensor([-0.0031,  0.0173])\n",
      "\tparams: tensor([  5.3498, -17.2033])\n",
      "Epoch: 3031,Loss: 2.928548\n",
      "\tgrad: tensor([-0.0031,  0.0172])\n",
      "\tparams: tensor([  5.3498, -17.2035])\n",
      "Epoch: 3032,Loss: 2.928545\n",
      "\tgrad: tensor([-0.0030,  0.0172])\n",
      "\tparams: tensor([  5.3498, -17.2036])\n",
      "Epoch: 3033,Loss: 2.928543\n",
      "\tgrad: tensor([-0.0030,  0.0172])\n",
      "\tparams: tensor([  5.3499, -17.2038])\n",
      "Epoch: 3034,Loss: 2.928539\n",
      "\tgrad: tensor([-0.0030,  0.0172])\n",
      "\tparams: tensor([  5.3499, -17.2040])\n",
      "Epoch: 3035,Loss: 2.928536\n",
      "\tgrad: tensor([-0.0030,  0.0171])\n",
      "\tparams: tensor([  5.3499, -17.2041])\n",
      "Epoch: 3036,Loss: 2.928532\n",
      "\tgrad: tensor([-0.0030,  0.0171])\n",
      "\tparams: tensor([  5.3500, -17.2043])\n",
      "Epoch: 3037,Loss: 2.928531\n",
      "\tgrad: tensor([-0.0030,  0.0171])\n",
      "\tparams: tensor([  5.3500, -17.2045])\n",
      "Epoch: 3038,Loss: 2.928528\n",
      "\tgrad: tensor([-0.0030,  0.0170])\n",
      "\tparams: tensor([  5.3500, -17.2047])\n",
      "Epoch: 3039,Loss: 2.928524\n",
      "\tgrad: tensor([-0.0030,  0.0170])\n",
      "\tparams: tensor([  5.3501, -17.2048])\n",
      "Epoch: 3040,Loss: 2.928521\n",
      "\tgrad: tensor([-0.0030,  0.0170])\n",
      "\tparams: tensor([  5.3501, -17.2050])\n",
      "Epoch: 3041,Loss: 2.928519\n",
      "\tgrad: tensor([-0.0030,  0.0170])\n",
      "\tparams: tensor([  5.3501, -17.2052])\n",
      "Epoch: 3042,Loss: 2.928514\n",
      "\tgrad: tensor([-0.0030,  0.0169])\n",
      "\tparams: tensor([  5.3502, -17.2053])\n",
      "Epoch: 3043,Loss: 2.928512\n",
      "\tgrad: tensor([-0.0030,  0.0169])\n",
      "\tparams: tensor([  5.3502, -17.2055])\n",
      "Epoch: 3044,Loss: 2.928509\n",
      "\tgrad: tensor([-0.0030,  0.0169])\n",
      "\tparams: tensor([  5.3502, -17.2057])\n",
      "Epoch: 3045,Loss: 2.928505\n",
      "\tgrad: tensor([-0.0030,  0.0168])\n",
      "\tparams: tensor([  5.3502, -17.2058])\n",
      "Epoch: 3046,Loss: 2.928503\n",
      "\tgrad: tensor([-0.0030,  0.0168])\n",
      "\tparams: tensor([  5.3503, -17.2060])\n",
      "Epoch: 3047,Loss: 2.928500\n",
      "\tgrad: tensor([-0.0030,  0.0168])\n",
      "\tparams: tensor([  5.3503, -17.2062])\n",
      "Epoch: 3048,Loss: 2.928498\n",
      "\tgrad: tensor([-0.0030,  0.0168])\n",
      "\tparams: tensor([  5.3503, -17.2063])\n",
      "Epoch: 3049,Loss: 2.928495\n",
      "\tgrad: tensor([-0.0030,  0.0167])\n",
      "\tparams: tensor([  5.3504, -17.2065])\n",
      "Epoch: 3050,Loss: 2.928491\n",
      "\tgrad: tensor([-0.0030,  0.0167])\n",
      "\tparams: tensor([  5.3504, -17.2067])\n",
      "Epoch: 3051,Loss: 2.928489\n",
      "\tgrad: tensor([-0.0030,  0.0167])\n",
      "\tparams: tensor([  5.3504, -17.2068])\n",
      "Epoch: 3052,Loss: 2.928486\n",
      "\tgrad: tensor([-0.0029,  0.0166])\n",
      "\tparams: tensor([  5.3504, -17.2070])\n",
      "Epoch: 3053,Loss: 2.928484\n",
      "\tgrad: tensor([-0.0029,  0.0166])\n",
      "\tparams: tensor([  5.3505, -17.2072])\n",
      "Epoch: 3054,Loss: 2.928481\n",
      "\tgrad: tensor([-0.0029,  0.0166])\n",
      "\tparams: tensor([  5.3505, -17.2073])\n",
      "Epoch: 3055,Loss: 2.928477\n",
      "\tgrad: tensor([-0.0029,  0.0165])\n",
      "\tparams: tensor([  5.3505, -17.2075])\n",
      "Epoch: 3056,Loss: 2.928474\n",
      "\tgrad: tensor([-0.0029,  0.0165])\n",
      "\tparams: tensor([  5.3506, -17.2077])\n",
      "Epoch: 3057,Loss: 2.928472\n",
      "\tgrad: tensor([-0.0029,  0.0165])\n",
      "\tparams: tensor([  5.3506, -17.2078])\n",
      "Epoch: 3058,Loss: 2.928469\n",
      "\tgrad: tensor([-0.0029,  0.0165])\n",
      "\tparams: tensor([  5.3506, -17.2080])\n",
      "Epoch: 3059,Loss: 2.928468\n",
      "\tgrad: tensor([-0.0029,  0.0164])\n",
      "\tparams: tensor([  5.3507, -17.2082])\n",
      "Epoch: 3060,Loss: 2.928463\n",
      "\tgrad: tensor([-0.0029,  0.0164])\n",
      "\tparams: tensor([  5.3507, -17.2083])\n",
      "Epoch: 3061,Loss: 2.928460\n",
      "\tgrad: tensor([-0.0029,  0.0164])\n",
      "\tparams: tensor([  5.3507, -17.2085])\n",
      "Epoch: 3062,Loss: 2.928458\n",
      "\tgrad: tensor([-0.0029,  0.0164])\n",
      "\tparams: tensor([  5.3507, -17.2087])\n",
      "Epoch: 3063,Loss: 2.928456\n",
      "\tgrad: tensor([-0.0029,  0.0163])\n",
      "\tparams: tensor([  5.3508, -17.2088])\n",
      "Epoch: 3064,Loss: 2.928452\n",
      "\tgrad: tensor([-0.0029,  0.0163])\n",
      "\tparams: tensor([  5.3508, -17.2090])\n",
      "Epoch: 3065,Loss: 2.928449\n",
      "\tgrad: tensor([-0.0029,  0.0163])\n",
      "\tparams: tensor([  5.3508, -17.2091])\n",
      "Epoch: 3066,Loss: 2.928447\n",
      "\tgrad: tensor([-0.0029,  0.0162])\n",
      "\tparams: tensor([  5.3509, -17.2093])\n",
      "Epoch: 3067,Loss: 2.928443\n",
      "\tgrad: tensor([-0.0029,  0.0162])\n",
      "\tparams: tensor([  5.3509, -17.2095])\n",
      "Epoch: 3068,Loss: 2.928444\n",
      "\tgrad: tensor([-0.0029,  0.0162])\n",
      "\tparams: tensor([  5.3509, -17.2096])\n",
      "Epoch: 3069,Loss: 2.928440\n",
      "\tgrad: tensor([-0.0029,  0.0162])\n",
      "\tparams: tensor([  5.3509, -17.2098])\n",
      "Epoch: 3070,Loss: 2.928435\n",
      "\tgrad: tensor([-0.0029,  0.0161])\n",
      "\tparams: tensor([  5.3510, -17.2100])\n",
      "Epoch: 3071,Loss: 2.928435\n",
      "\tgrad: tensor([-0.0029,  0.0161])\n",
      "\tparams: tensor([  5.3510, -17.2101])\n",
      "Epoch: 3072,Loss: 2.928430\n",
      "\tgrad: tensor([-0.0028,  0.0161])\n",
      "\tparams: tensor([  5.3510, -17.2103])\n",
      "Epoch: 3073,Loss: 2.928428\n",
      "\tgrad: tensor([-0.0028,  0.0161])\n",
      "\tparams: tensor([  5.3511, -17.2104])\n",
      "Epoch: 3074,Loss: 2.928426\n",
      "\tgrad: tensor([-0.0028,  0.0160])\n",
      "\tparams: tensor([  5.3511, -17.2106])\n",
      "Epoch: 3075,Loss: 2.928423\n",
      "\tgrad: tensor([-0.0028,  0.0160])\n",
      "\tparams: tensor([  5.3511, -17.2108])\n",
      "Epoch: 3076,Loss: 2.928421\n",
      "\tgrad: tensor([-0.0028,  0.0160])\n",
      "\tparams: tensor([  5.3511, -17.2109])\n",
      "Epoch: 3077,Loss: 2.928417\n",
      "\tgrad: tensor([-0.0028,  0.0159])\n",
      "\tparams: tensor([  5.3512, -17.2111])\n",
      "Epoch: 3078,Loss: 2.928416\n",
      "\tgrad: tensor([-0.0028,  0.0159])\n",
      "\tparams: tensor([  5.3512, -17.2112])\n",
      "Epoch: 3079,Loss: 2.928411\n",
      "\tgrad: tensor([-0.0028,  0.0159])\n",
      "\tparams: tensor([  5.3512, -17.2114])\n",
      "Epoch: 3080,Loss: 2.928410\n",
      "\tgrad: tensor([-0.0028,  0.0159])\n",
      "\tparams: tensor([  5.3512, -17.2116])\n",
      "Epoch: 3081,Loss: 2.928407\n",
      "\tgrad: tensor([-0.0028,  0.0158])\n",
      "\tparams: tensor([  5.3513, -17.2117])\n",
      "Epoch: 3082,Loss: 2.928404\n",
      "\tgrad: tensor([-0.0028,  0.0158])\n",
      "\tparams: tensor([  5.3513, -17.2119])\n",
      "Epoch: 3083,Loss: 2.928402\n",
      "\tgrad: tensor([-0.0028,  0.0158])\n",
      "\tparams: tensor([  5.3513, -17.2120])\n",
      "Epoch: 3084,Loss: 2.928399\n",
      "\tgrad: tensor([-0.0028,  0.0158])\n",
      "\tparams: tensor([  5.3514, -17.2122])\n",
      "Epoch: 3085,Loss: 2.928396\n",
      "\tgrad: tensor([-0.0028,  0.0157])\n",
      "\tparams: tensor([  5.3514, -17.2123])\n",
      "Epoch: 3086,Loss: 2.928395\n",
      "\tgrad: tensor([-0.0028,  0.0157])\n",
      "\tparams: tensor([  5.3514, -17.2125])\n",
      "Epoch: 3087,Loss: 2.928392\n",
      "\tgrad: tensor([-0.0027,  0.0157])\n",
      "\tparams: tensor([  5.3514, -17.2127])\n",
      "Epoch: 3088,Loss: 2.928389\n",
      "\tgrad: tensor([-0.0027,  0.0157])\n",
      "\tparams: tensor([  5.3515, -17.2128])\n",
      "Epoch: 3089,Loss: 2.928386\n",
      "\tgrad: tensor([-0.0027,  0.0156])\n",
      "\tparams: tensor([  5.3515, -17.2130])\n",
      "Epoch: 3090,Loss: 2.928383\n",
      "\tgrad: tensor([-0.0028,  0.0156])\n",
      "\tparams: tensor([  5.3515, -17.2131])\n",
      "Epoch: 3091,Loss: 2.928382\n",
      "\tgrad: tensor([-0.0028,  0.0156])\n",
      "\tparams: tensor([  5.3516, -17.2133])\n",
      "Epoch: 3092,Loss: 2.928379\n",
      "\tgrad: tensor([-0.0027,  0.0155])\n",
      "\tparams: tensor([  5.3516, -17.2134])\n",
      "Epoch: 3093,Loss: 2.928378\n",
      "\tgrad: tensor([-0.0027,  0.0155])\n",
      "\tparams: tensor([  5.3516, -17.2136])\n",
      "Epoch: 3094,Loss: 2.928375\n",
      "\tgrad: tensor([-0.0027,  0.0155])\n",
      "\tparams: tensor([  5.3516, -17.2137])\n",
      "Epoch: 3095,Loss: 2.928372\n",
      "\tgrad: tensor([-0.0027,  0.0155])\n",
      "\tparams: tensor([  5.3517, -17.2139])\n",
      "Epoch: 3096,Loss: 2.928370\n",
      "\tgrad: tensor([-0.0027,  0.0154])\n",
      "\tparams: tensor([  5.3517, -17.2141])\n",
      "Epoch: 3097,Loss: 2.928368\n",
      "\tgrad: tensor([-0.0027,  0.0154])\n",
      "\tparams: tensor([  5.3517, -17.2142])\n",
      "Epoch: 3098,Loss: 2.928364\n",
      "\tgrad: tensor([-0.0027,  0.0154])\n",
      "\tparams: tensor([  5.3517, -17.2144])\n",
      "Epoch: 3099,Loss: 2.928362\n",
      "\tgrad: tensor([-0.0027,  0.0154])\n",
      "\tparams: tensor([  5.3518, -17.2145])\n",
      "Epoch: 3100,Loss: 2.928361\n",
      "\tgrad: tensor([-0.0027,  0.0153])\n",
      "\tparams: tensor([  5.3518, -17.2147])\n",
      "Epoch: 3101,Loss: 2.928356\n",
      "\tgrad: tensor([-0.0027,  0.0153])\n",
      "\tparams: tensor([  5.3518, -17.2148])\n",
      "Epoch: 3102,Loss: 2.928355\n",
      "\tgrad: tensor([-0.0027,  0.0153])\n",
      "\tparams: tensor([  5.3519, -17.2150])\n",
      "Epoch: 3103,Loss: 2.928353\n",
      "\tgrad: tensor([-0.0027,  0.0153])\n",
      "\tparams: tensor([  5.3519, -17.2151])\n",
      "Epoch: 3104,Loss: 2.928349\n",
      "\tgrad: tensor([-0.0027,  0.0152])\n",
      "\tparams: tensor([  5.3519, -17.2153])\n",
      "Epoch: 3105,Loss: 2.928348\n",
      "\tgrad: tensor([-0.0027,  0.0152])\n",
      "\tparams: tensor([  5.3519, -17.2154])\n",
      "Epoch: 3106,Loss: 2.928345\n",
      "\tgrad: tensor([-0.0027,  0.0152])\n",
      "\tparams: tensor([  5.3520, -17.2156])\n",
      "Epoch: 3107,Loss: 2.928343\n",
      "\tgrad: tensor([-0.0027,  0.0152])\n",
      "\tparams: tensor([  5.3520, -17.2157])\n",
      "Epoch: 3108,Loss: 2.928340\n",
      "\tgrad: tensor([-0.0027,  0.0151])\n",
      "\tparams: tensor([  5.3520, -17.2159])\n",
      "Epoch: 3109,Loss: 2.928339\n",
      "\tgrad: tensor([-0.0027,  0.0151])\n",
      "\tparams: tensor([  5.3520, -17.2160])\n",
      "Epoch: 3110,Loss: 2.928337\n",
      "\tgrad: tensor([-0.0027,  0.0151])\n",
      "\tparams: tensor([  5.3521, -17.2162])\n",
      "Epoch: 3111,Loss: 2.928333\n",
      "\tgrad: tensor([-0.0027,  0.0151])\n",
      "\tparams: tensor([  5.3521, -17.2163])\n",
      "Epoch: 3112,Loss: 2.928332\n",
      "\tgrad: tensor([-0.0027,  0.0150])\n",
      "\tparams: tensor([  5.3521, -17.2165])\n",
      "Epoch: 3113,Loss: 2.928328\n",
      "\tgrad: tensor([-0.0026,  0.0150])\n",
      "\tparams: tensor([  5.3521, -17.2166])\n",
      "Epoch: 3114,Loss: 2.928329\n",
      "\tgrad: tensor([-0.0027,  0.0150])\n",
      "\tparams: tensor([  5.3522, -17.2168])\n",
      "Epoch: 3115,Loss: 2.928324\n",
      "\tgrad: tensor([-0.0026,  0.0149])\n",
      "\tparams: tensor([  5.3522, -17.2169])\n",
      "Epoch: 3116,Loss: 2.928323\n",
      "\tgrad: tensor([-0.0026,  0.0149])\n",
      "\tparams: tensor([  5.3522, -17.2171])\n",
      "Epoch: 3117,Loss: 2.928320\n",
      "\tgrad: tensor([-0.0026,  0.0149])\n",
      "\tparams: tensor([  5.3523, -17.2172])\n",
      "Epoch: 3118,Loss: 2.928319\n",
      "\tgrad: tensor([-0.0026,  0.0149])\n",
      "\tparams: tensor([  5.3523, -17.2174])\n",
      "Epoch: 3119,Loss: 2.928315\n",
      "\tgrad: tensor([-0.0026,  0.0148])\n",
      "\tparams: tensor([  5.3523, -17.2175])\n",
      "Epoch: 3120,Loss: 2.928313\n",
      "\tgrad: tensor([-0.0026,  0.0148])\n",
      "\tparams: tensor([  5.3523, -17.2177])\n",
      "Epoch: 3121,Loss: 2.928310\n",
      "\tgrad: tensor([-0.0026,  0.0148])\n",
      "\tparams: tensor([  5.3524, -17.2178])\n",
      "Epoch: 3122,Loss: 2.928308\n",
      "\tgrad: tensor([-0.0026,  0.0148])\n",
      "\tparams: tensor([  5.3524, -17.2180])\n",
      "Epoch: 3123,Loss: 2.928306\n",
      "\tgrad: tensor([-0.0026,  0.0147])\n",
      "\tparams: tensor([  5.3524, -17.2181])\n",
      "Epoch: 3124,Loss: 2.928304\n",
      "\tgrad: tensor([-0.0026,  0.0147])\n",
      "\tparams: tensor([  5.3524, -17.2183])\n",
      "Epoch: 3125,Loss: 2.928303\n",
      "\tgrad: tensor([-0.0026,  0.0147])\n",
      "\tparams: tensor([  5.3525, -17.2184])\n",
      "Epoch: 3126,Loss: 2.928299\n",
      "\tgrad: tensor([-0.0026,  0.0147])\n",
      "\tparams: tensor([  5.3525, -17.2186])\n",
      "Epoch: 3127,Loss: 2.928296\n",
      "\tgrad: tensor([-0.0026,  0.0146])\n",
      "\tparams: tensor([  5.3525, -17.2187])\n",
      "Epoch: 3128,Loss: 2.928295\n",
      "\tgrad: tensor([-0.0026,  0.0146])\n",
      "\tparams: tensor([  5.3525, -17.2189])\n",
      "Epoch: 3129,Loss: 2.928293\n",
      "\tgrad: tensor([-0.0026,  0.0146])\n",
      "\tparams: tensor([  5.3526, -17.2190])\n",
      "Epoch: 3130,Loss: 2.928291\n",
      "\tgrad: tensor([-0.0026,  0.0146])\n",
      "\tparams: tensor([  5.3526, -17.2192])\n",
      "Epoch: 3131,Loss: 2.928288\n",
      "\tgrad: tensor([-0.0026,  0.0145])\n",
      "\tparams: tensor([  5.3526, -17.2193])\n",
      "Epoch: 3132,Loss: 2.928287\n",
      "\tgrad: tensor([-0.0026,  0.0145])\n",
      "\tparams: tensor([  5.3526, -17.2194])\n",
      "Epoch: 3133,Loss: 2.928285\n",
      "\tgrad: tensor([-0.0025,  0.0145])\n",
      "\tparams: tensor([  5.3527, -17.2196])\n",
      "Epoch: 3134,Loss: 2.928282\n",
      "\tgrad: tensor([-0.0026,  0.0145])\n",
      "\tparams: tensor([  5.3527, -17.2197])\n",
      "Epoch: 3135,Loss: 2.928280\n",
      "\tgrad: tensor([-0.0026,  0.0144])\n",
      "\tparams: tensor([  5.3527, -17.2199])\n",
      "Epoch: 3136,Loss: 2.928276\n",
      "\tgrad: tensor([-0.0025,  0.0144])\n",
      "\tparams: tensor([  5.3527, -17.2200])\n",
      "Epoch: 3137,Loss: 2.928275\n",
      "\tgrad: tensor([-0.0026,  0.0144])\n",
      "\tparams: tensor([  5.3528, -17.2202])\n",
      "Epoch: 3138,Loss: 2.928273\n",
      "\tgrad: tensor([-0.0025,  0.0144])\n",
      "\tparams: tensor([  5.3528, -17.2203])\n",
      "Epoch: 3139,Loss: 2.928271\n",
      "\tgrad: tensor([-0.0025,  0.0144])\n",
      "\tparams: tensor([  5.3528, -17.2205])\n",
      "Epoch: 3140,Loss: 2.928268\n",
      "\tgrad: tensor([-0.0025,  0.0143])\n",
      "\tparams: tensor([  5.3528, -17.2206])\n",
      "Epoch: 3141,Loss: 2.928267\n",
      "\tgrad: tensor([-0.0025,  0.0143])\n",
      "\tparams: tensor([  5.3529, -17.2207])\n",
      "Epoch: 3142,Loss: 2.928264\n",
      "\tgrad: tensor([-0.0025,  0.0143])\n",
      "\tparams: tensor([  5.3529, -17.2209])\n",
      "Epoch: 3143,Loss: 2.928263\n",
      "\tgrad: tensor([-0.0025,  0.0143])\n",
      "\tparams: tensor([  5.3529, -17.2210])\n",
      "Epoch: 3144,Loss: 2.928260\n",
      "\tgrad: tensor([-0.0025,  0.0142])\n",
      "\tparams: tensor([  5.3529, -17.2212])\n",
      "Epoch: 3145,Loss: 2.928259\n",
      "\tgrad: tensor([-0.0025,  0.0142])\n",
      "\tparams: tensor([  5.3530, -17.2213])\n",
      "Epoch: 3146,Loss: 2.928256\n",
      "\tgrad: tensor([-0.0025,  0.0142])\n",
      "\tparams: tensor([  5.3530, -17.2214])\n",
      "Epoch: 3147,Loss: 2.928255\n",
      "\tgrad: tensor([-0.0025,  0.0142])\n",
      "\tparams: tensor([  5.3530, -17.2216])\n",
      "Epoch: 3148,Loss: 2.928252\n",
      "\tgrad: tensor([-0.0025,  0.0141])\n",
      "\tparams: tensor([  5.3530, -17.2217])\n",
      "Epoch: 3149,Loss: 2.928250\n",
      "\tgrad: tensor([-0.0025,  0.0141])\n",
      "\tparams: tensor([  5.3531, -17.2219])\n",
      "Epoch: 3150,Loss: 2.928249\n",
      "\tgrad: tensor([-0.0025,  0.0141])\n",
      "\tparams: tensor([  5.3531, -17.2220])\n",
      "Epoch: 3151,Loss: 2.928246\n",
      "\tgrad: tensor([-0.0025,  0.0141])\n",
      "\tparams: tensor([  5.3531, -17.2222])\n",
      "Epoch: 3152,Loss: 2.928245\n",
      "\tgrad: tensor([-0.0025,  0.0140])\n",
      "\tparams: tensor([  5.3531, -17.2223])\n",
      "Epoch: 3153,Loss: 2.928242\n",
      "\tgrad: tensor([-0.0025,  0.0140])\n",
      "\tparams: tensor([  5.3532, -17.2224])\n",
      "Epoch: 3154,Loss: 2.928239\n",
      "\tgrad: tensor([-0.0025,  0.0140])\n",
      "\tparams: tensor([  5.3532, -17.2226])\n",
      "Epoch: 3155,Loss: 2.928236\n",
      "\tgrad: tensor([-0.0025,  0.0140])\n",
      "\tparams: tensor([  5.3532, -17.2227])\n",
      "Epoch: 3156,Loss: 2.928236\n",
      "\tgrad: tensor([-0.0024,  0.0139])\n",
      "\tparams: tensor([  5.3532, -17.2229])\n",
      "Epoch: 3157,Loss: 2.928233\n",
      "\tgrad: tensor([-0.0025,  0.0139])\n",
      "\tparams: tensor([  5.3533, -17.2230])\n",
      "Epoch: 3158,Loss: 2.928231\n",
      "\tgrad: tensor([-0.0024,  0.0139])\n",
      "\tparams: tensor([  5.3533, -17.2231])\n",
      "Epoch: 3159,Loss: 2.928230\n",
      "\tgrad: tensor([-0.0025,  0.0139])\n",
      "\tparams: tensor([  5.3533, -17.2233])\n",
      "Epoch: 3160,Loss: 2.928227\n",
      "\tgrad: tensor([-0.0024,  0.0138])\n",
      "\tparams: tensor([  5.3533, -17.2234])\n",
      "Epoch: 3161,Loss: 2.928226\n",
      "\tgrad: tensor([-0.0025,  0.0138])\n",
      "\tparams: tensor([  5.3534, -17.2235])\n",
      "Epoch: 3162,Loss: 2.928225\n",
      "\tgrad: tensor([-0.0024,  0.0138])\n",
      "\tparams: tensor([  5.3534, -17.2237])\n",
      "Epoch: 3163,Loss: 2.928222\n",
      "\tgrad: tensor([-0.0024,  0.0138])\n",
      "\tparams: tensor([  5.3534, -17.2238])\n",
      "Epoch: 3164,Loss: 2.928219\n",
      "\tgrad: tensor([-0.0024,  0.0138])\n",
      "\tparams: tensor([  5.3534, -17.2240])\n",
      "Epoch: 3165,Loss: 2.928218\n",
      "\tgrad: tensor([-0.0024,  0.0137])\n",
      "\tparams: tensor([  5.3535, -17.2241])\n",
      "Epoch: 3166,Loss: 2.928216\n",
      "\tgrad: tensor([-0.0024,  0.0137])\n",
      "\tparams: tensor([  5.3535, -17.2242])\n",
      "Epoch: 3167,Loss: 2.928215\n",
      "\tgrad: tensor([-0.0024,  0.0137])\n",
      "\tparams: tensor([  5.3535, -17.2244])\n",
      "Epoch: 3168,Loss: 2.928212\n",
      "\tgrad: tensor([-0.0024,  0.0137])\n",
      "\tparams: tensor([  5.3535, -17.2245])\n",
      "Epoch: 3169,Loss: 2.928211\n",
      "\tgrad: tensor([-0.0024,  0.0136])\n",
      "\tparams: tensor([  5.3536, -17.2246])\n",
      "Epoch: 3170,Loss: 2.928209\n",
      "\tgrad: tensor([-0.0024,  0.0136])\n",
      "\tparams: tensor([  5.3536, -17.2248])\n",
      "Epoch: 3171,Loss: 2.928206\n",
      "\tgrad: tensor([-0.0024,  0.0136])\n",
      "\tparams: tensor([  5.3536, -17.2249])\n",
      "Epoch: 3172,Loss: 2.928205\n",
      "\tgrad: tensor([-0.0024,  0.0136])\n",
      "\tparams: tensor([  5.3536, -17.2250])\n",
      "Epoch: 3173,Loss: 2.928204\n",
      "\tgrad: tensor([-0.0024,  0.0135])\n",
      "\tparams: tensor([  5.3537, -17.2252])\n",
      "Epoch: 3174,Loss: 2.928202\n",
      "\tgrad: tensor([-0.0024,  0.0135])\n",
      "\tparams: tensor([  5.3537, -17.2253])\n",
      "Epoch: 3175,Loss: 2.928200\n",
      "\tgrad: tensor([-0.0024,  0.0135])\n",
      "\tparams: tensor([  5.3537, -17.2255])\n",
      "Epoch: 3176,Loss: 2.928196\n",
      "\tgrad: tensor([-0.0024,  0.0135])\n",
      "\tparams: tensor([  5.3537, -17.2256])\n",
      "Epoch: 3177,Loss: 2.928195\n",
      "\tgrad: tensor([-0.0024,  0.0134])\n",
      "\tparams: tensor([  5.3538, -17.2257])\n",
      "Epoch: 3178,Loss: 2.928195\n",
      "\tgrad: tensor([-0.0024,  0.0134])\n",
      "\tparams: tensor([  5.3538, -17.2259])\n",
      "Epoch: 3179,Loss: 2.928191\n",
      "\tgrad: tensor([-0.0024,  0.0134])\n",
      "\tparams: tensor([  5.3538, -17.2260])\n",
      "Epoch: 3180,Loss: 2.928190\n",
      "\tgrad: tensor([-0.0024,  0.0134])\n",
      "\tparams: tensor([  5.3538, -17.2261])\n",
      "Epoch: 3181,Loss: 2.928188\n",
      "\tgrad: tensor([-0.0023,  0.0134])\n",
      "\tparams: tensor([  5.3538, -17.2263])\n",
      "Epoch: 3182,Loss: 2.928186\n",
      "\tgrad: tensor([-0.0023,  0.0133])\n",
      "\tparams: tensor([  5.3539, -17.2264])\n",
      "Epoch: 3183,Loss: 2.928185\n",
      "\tgrad: tensor([-0.0024,  0.0133])\n",
      "\tparams: tensor([  5.3539, -17.2265])\n",
      "Epoch: 3184,Loss: 2.928184\n",
      "\tgrad: tensor([-0.0023,  0.0133])\n",
      "\tparams: tensor([  5.3539, -17.2267])\n",
      "Epoch: 3185,Loss: 2.928182\n",
      "\tgrad: tensor([-0.0024,  0.0133])\n",
      "\tparams: tensor([  5.3539, -17.2268])\n",
      "Epoch: 3186,Loss: 2.928180\n",
      "\tgrad: tensor([-0.0024,  0.0132])\n",
      "\tparams: tensor([  5.3540, -17.2269])\n",
      "Epoch: 3187,Loss: 2.928178\n",
      "\tgrad: tensor([-0.0023,  0.0132])\n",
      "\tparams: tensor([  5.3540, -17.2271])\n",
      "Epoch: 3188,Loss: 2.928175\n",
      "\tgrad: tensor([-0.0023,  0.0132])\n",
      "\tparams: tensor([  5.3540, -17.2272])\n",
      "Epoch: 3189,Loss: 2.928172\n",
      "\tgrad: tensor([-0.0023,  0.0132])\n",
      "\tparams: tensor([  5.3540, -17.2273])\n",
      "Epoch: 3190,Loss: 2.928171\n",
      "\tgrad: tensor([-0.0023,  0.0132])\n",
      "\tparams: tensor([  5.3541, -17.2275])\n",
      "Epoch: 3191,Loss: 2.928170\n",
      "\tgrad: tensor([-0.0023,  0.0131])\n",
      "\tparams: tensor([  5.3541, -17.2276])\n",
      "Epoch: 3192,Loss: 2.928169\n",
      "\tgrad: tensor([-0.0023,  0.0131])\n",
      "\tparams: tensor([  5.3541, -17.2277])\n",
      "Epoch: 3193,Loss: 2.928167\n",
      "\tgrad: tensor([-0.0023,  0.0131])\n",
      "\tparams: tensor([  5.3541, -17.2278])\n",
      "Epoch: 3194,Loss: 2.928164\n",
      "\tgrad: tensor([-0.0023,  0.0131])\n",
      "\tparams: tensor([  5.3542, -17.2280])\n",
      "Epoch: 3195,Loss: 2.928163\n",
      "\tgrad: tensor([-0.0023,  0.0130])\n",
      "\tparams: tensor([  5.3542, -17.2281])\n",
      "Epoch: 3196,Loss: 2.928162\n",
      "\tgrad: tensor([-0.0023,  0.0130])\n",
      "\tparams: tensor([  5.3542, -17.2282])\n",
      "Epoch: 3197,Loss: 2.928160\n",
      "\tgrad: tensor([-0.0023,  0.0130])\n",
      "\tparams: tensor([  5.3542, -17.2284])\n",
      "Epoch: 3198,Loss: 2.928158\n",
      "\tgrad: tensor([-0.0023,  0.0130])\n",
      "\tparams: tensor([  5.3542, -17.2285])\n",
      "Epoch: 3199,Loss: 2.928157\n",
      "\tgrad: tensor([-0.0023,  0.0130])\n",
      "\tparams: tensor([  5.3543, -17.2286])\n",
      "Epoch: 3200,Loss: 2.928154\n",
      "\tgrad: tensor([-0.0023,  0.0129])\n",
      "\tparams: tensor([  5.3543, -17.2288])\n",
      "Epoch: 3201,Loss: 2.928152\n",
      "\tgrad: tensor([-0.0023,  0.0129])\n",
      "\tparams: tensor([  5.3543, -17.2289])\n",
      "Epoch: 3202,Loss: 2.928149\n",
      "\tgrad: tensor([-0.0023,  0.0129])\n",
      "\tparams: tensor([  5.3543, -17.2290])\n",
      "Epoch: 3203,Loss: 2.928150\n",
      "\tgrad: tensor([-0.0023,  0.0129])\n",
      "\tparams: tensor([  5.3544, -17.2291])\n",
      "Epoch: 3204,Loss: 2.928147\n",
      "\tgrad: tensor([-0.0022,  0.0129])\n",
      "\tparams: tensor([  5.3544, -17.2293])\n",
      "Epoch: 3205,Loss: 2.928146\n",
      "\tgrad: tensor([-0.0023,  0.0128])\n",
      "\tparams: tensor([  5.3544, -17.2294])\n",
      "Epoch: 3206,Loss: 2.928144\n",
      "\tgrad: tensor([-0.0023,  0.0128])\n",
      "\tparams: tensor([  5.3544, -17.2295])\n",
      "Epoch: 3207,Loss: 2.928142\n",
      "\tgrad: tensor([-0.0023,  0.0128])\n",
      "\tparams: tensor([  5.3544, -17.2297])\n",
      "Epoch: 3208,Loss: 2.928140\n",
      "\tgrad: tensor([-0.0022,  0.0128])\n",
      "\tparams: tensor([  5.3545, -17.2298])\n",
      "Epoch: 3209,Loss: 2.928138\n",
      "\tgrad: tensor([-0.0022,  0.0127])\n",
      "\tparams: tensor([  5.3545, -17.2299])\n",
      "Epoch: 3210,Loss: 2.928137\n",
      "\tgrad: tensor([-0.0023,  0.0127])\n",
      "\tparams: tensor([  5.3545, -17.2300])\n",
      "Epoch: 3211,Loss: 2.928135\n",
      "\tgrad: tensor([-0.0023,  0.0127])\n",
      "\tparams: tensor([  5.3545, -17.2302])\n",
      "Epoch: 3212,Loss: 2.928135\n",
      "\tgrad: tensor([-0.0023,  0.0127])\n",
      "\tparams: tensor([  5.3546, -17.2303])\n",
      "Epoch: 3213,Loss: 2.928133\n",
      "\tgrad: tensor([-0.0022,  0.0127])\n",
      "\tparams: tensor([  5.3546, -17.2304])\n",
      "Epoch: 3214,Loss: 2.928131\n",
      "\tgrad: tensor([-0.0022,  0.0126])\n",
      "\tparams: tensor([  5.3546, -17.2305])\n",
      "Epoch: 3215,Loss: 2.928130\n",
      "\tgrad: tensor([-0.0022,  0.0126])\n",
      "\tparams: tensor([  5.3546, -17.2307])\n",
      "Epoch: 3216,Loss: 2.928126\n",
      "\tgrad: tensor([-0.0022,  0.0126])\n",
      "\tparams: tensor([  5.3546, -17.2308])\n",
      "Epoch: 3217,Loss: 2.928125\n",
      "\tgrad: tensor([-0.0022,  0.0126])\n",
      "\tparams: tensor([  5.3547, -17.2309])\n",
      "Epoch: 3218,Loss: 2.928124\n",
      "\tgrad: tensor([-0.0022,  0.0125])\n",
      "\tparams: tensor([  5.3547, -17.2310])\n",
      "Epoch: 3219,Loss: 2.928121\n",
      "\tgrad: tensor([-0.0022,  0.0125])\n",
      "\tparams: tensor([  5.3547, -17.2312])\n",
      "Epoch: 3220,Loss: 2.928121\n",
      "\tgrad: tensor([-0.0022,  0.0125])\n",
      "\tparams: tensor([  5.3547, -17.2313])\n",
      "Epoch: 3221,Loss: 2.928120\n",
      "\tgrad: tensor([-0.0022,  0.0125])\n",
      "\tparams: tensor([  5.3548, -17.2314])\n",
      "Epoch: 3222,Loss: 2.928118\n",
      "\tgrad: tensor([-0.0022,  0.0125])\n",
      "\tparams: tensor([  5.3548, -17.2315])\n",
      "Epoch: 3223,Loss: 2.928117\n",
      "\tgrad: tensor([-0.0022,  0.0124])\n",
      "\tparams: tensor([  5.3548, -17.2317])\n",
      "Epoch: 3224,Loss: 2.928115\n",
      "\tgrad: tensor([-0.0022,  0.0124])\n",
      "\tparams: tensor([  5.3548, -17.2318])\n",
      "Epoch: 3225,Loss: 2.928113\n",
      "\tgrad: tensor([-0.0022,  0.0124])\n",
      "\tparams: tensor([  5.3548, -17.2319])\n",
      "Epoch: 3226,Loss: 2.928110\n",
      "\tgrad: tensor([-0.0022,  0.0124])\n",
      "\tparams: tensor([  5.3549, -17.2320])\n",
      "Epoch: 3227,Loss: 2.928109\n",
      "\tgrad: tensor([-0.0022,  0.0124])\n",
      "\tparams: tensor([  5.3549, -17.2322])\n",
      "Epoch: 3228,Loss: 2.928108\n",
      "\tgrad: tensor([-0.0022,  0.0123])\n",
      "\tparams: tensor([  5.3549, -17.2323])\n",
      "Epoch: 3229,Loss: 2.928105\n",
      "\tgrad: tensor([-0.0022,  0.0123])\n",
      "\tparams: tensor([  5.3549, -17.2324])\n",
      "Epoch: 3230,Loss: 2.928105\n",
      "\tgrad: tensor([-0.0022,  0.0123])\n",
      "\tparams: tensor([  5.3550, -17.2325])\n",
      "Epoch: 3231,Loss: 2.928104\n",
      "\tgrad: tensor([-0.0022,  0.0123])\n",
      "\tparams: tensor([  5.3550, -17.2327])\n",
      "Epoch: 3232,Loss: 2.928102\n",
      "\tgrad: tensor([-0.0021,  0.0123])\n",
      "\tparams: tensor([  5.3550, -17.2328])\n",
      "Epoch: 3233,Loss: 2.928101\n",
      "\tgrad: tensor([-0.0022,  0.0122])\n",
      "\tparams: tensor([  5.3550, -17.2329])\n",
      "Epoch: 3234,Loss: 2.928098\n",
      "\tgrad: tensor([-0.0022,  0.0122])\n",
      "\tparams: tensor([  5.3550, -17.2330])\n",
      "Epoch: 3235,Loss: 2.928097\n",
      "\tgrad: tensor([-0.0022,  0.0122])\n",
      "\tparams: tensor([  5.3551, -17.2331])\n",
      "Epoch: 3236,Loss: 2.928095\n",
      "\tgrad: tensor([-0.0022,  0.0122])\n",
      "\tparams: tensor([  5.3551, -17.2333])\n",
      "Epoch: 3237,Loss: 2.928094\n",
      "\tgrad: tensor([-0.0022,  0.0121])\n",
      "\tparams: tensor([  5.3551, -17.2334])\n",
      "Epoch: 3238,Loss: 2.928093\n",
      "\tgrad: tensor([-0.0022,  0.0121])\n",
      "\tparams: tensor([  5.3551, -17.2335])\n",
      "Epoch: 3239,Loss: 2.928091\n",
      "\tgrad: tensor([-0.0022,  0.0121])\n",
      "\tparams: tensor([  5.3551, -17.2336])\n",
      "Epoch: 3240,Loss: 2.928090\n",
      "\tgrad: tensor([-0.0021,  0.0121])\n",
      "\tparams: tensor([  5.3552, -17.2338])\n",
      "Epoch: 3241,Loss: 2.928088\n",
      "\tgrad: tensor([-0.0021,  0.0121])\n",
      "\tparams: tensor([  5.3552, -17.2339])\n",
      "Epoch: 3242,Loss: 2.928086\n",
      "\tgrad: tensor([-0.0021,  0.0120])\n",
      "\tparams: tensor([  5.3552, -17.2340])\n",
      "Epoch: 3243,Loss: 2.928085\n",
      "\tgrad: tensor([-0.0021,  0.0120])\n",
      "\tparams: tensor([  5.3552, -17.2341])\n",
      "Epoch: 3244,Loss: 2.928084\n",
      "\tgrad: tensor([-0.0021,  0.0120])\n",
      "\tparams: tensor([  5.3553, -17.2342])\n",
      "Epoch: 3245,Loss: 2.928082\n",
      "\tgrad: tensor([-0.0021,  0.0120])\n",
      "\tparams: tensor([  5.3553, -17.2344])\n",
      "Epoch: 3246,Loss: 2.928080\n",
      "\tgrad: tensor([-0.0021,  0.0120])\n",
      "\tparams: tensor([  5.3553, -17.2345])\n",
      "Epoch: 3247,Loss: 2.928079\n",
      "\tgrad: tensor([-0.0021,  0.0119])\n",
      "\tparams: tensor([  5.3553, -17.2346])\n",
      "Epoch: 3248,Loss: 2.928076\n",
      "\tgrad: tensor([-0.0021,  0.0119])\n",
      "\tparams: tensor([  5.3553, -17.2347])\n",
      "Epoch: 3249,Loss: 2.928077\n",
      "\tgrad: tensor([-0.0021,  0.0119])\n",
      "\tparams: tensor([  5.3554, -17.2348])\n",
      "Epoch: 3250,Loss: 2.928075\n",
      "\tgrad: tensor([-0.0021,  0.0119])\n",
      "\tparams: tensor([  5.3554, -17.2350])\n",
      "Epoch: 3251,Loss: 2.928072\n",
      "\tgrad: tensor([-0.0021,  0.0119])\n",
      "\tparams: tensor([  5.3554, -17.2351])\n",
      "Epoch: 3252,Loss: 2.928072\n",
      "\tgrad: tensor([-0.0021,  0.0118])\n",
      "\tparams: tensor([  5.3554, -17.2352])\n",
      "Epoch: 3253,Loss: 2.928071\n",
      "\tgrad: tensor([-0.0021,  0.0118])\n",
      "\tparams: tensor([  5.3554, -17.2353])\n",
      "Epoch: 3254,Loss: 2.928068\n",
      "\tgrad: tensor([-0.0021,  0.0118])\n",
      "\tparams: tensor([  5.3555, -17.2354])\n",
      "Epoch: 3255,Loss: 2.928069\n",
      "\tgrad: tensor([-0.0021,  0.0118])\n",
      "\tparams: tensor([  5.3555, -17.2355])\n",
      "Epoch: 3256,Loss: 2.928066\n",
      "\tgrad: tensor([-0.0021,  0.0118])\n",
      "\tparams: tensor([  5.3555, -17.2357])\n",
      "Epoch: 3257,Loss: 2.928065\n",
      "\tgrad: tensor([-0.0021,  0.0117])\n",
      "\tparams: tensor([  5.3555, -17.2358])\n",
      "Epoch: 3258,Loss: 2.928064\n",
      "\tgrad: tensor([-0.0021,  0.0117])\n",
      "\tparams: tensor([  5.3555, -17.2359])\n",
      "Epoch: 3259,Loss: 2.928061\n",
      "\tgrad: tensor([-0.0021,  0.0117])\n",
      "\tparams: tensor([  5.3556, -17.2360])\n",
      "Epoch: 3260,Loss: 2.928060\n",
      "\tgrad: tensor([-0.0021,  0.0117])\n",
      "\tparams: tensor([  5.3556, -17.2361])\n",
      "Epoch: 3261,Loss: 2.928057\n",
      "\tgrad: tensor([-0.0021,  0.0117])\n",
      "\tparams: tensor([  5.3556, -17.2362])\n",
      "Epoch: 3262,Loss: 2.928058\n",
      "\tgrad: tensor([-0.0021,  0.0116])\n",
      "\tparams: tensor([  5.3556, -17.2364])\n",
      "Epoch: 3263,Loss: 2.928056\n",
      "\tgrad: tensor([-0.0021,  0.0116])\n",
      "\tparams: tensor([  5.3557, -17.2365])\n",
      "Epoch: 3264,Loss: 2.928055\n",
      "\tgrad: tensor([-0.0021,  0.0116])\n",
      "\tparams: tensor([  5.3557, -17.2366])\n",
      "Epoch: 3265,Loss: 2.928052\n",
      "\tgrad: tensor([-0.0021,  0.0116])\n",
      "\tparams: tensor([  5.3557, -17.2367])\n",
      "Epoch: 3266,Loss: 2.928053\n",
      "\tgrad: tensor([-0.0021,  0.0116])\n",
      "\tparams: tensor([  5.3557, -17.2368])\n",
      "Epoch: 3267,Loss: 2.928051\n",
      "\tgrad: tensor([-0.0021,  0.0115])\n",
      "\tparams: tensor([  5.3557, -17.2369])\n",
      "Epoch: 3268,Loss: 2.928050\n",
      "\tgrad: tensor([-0.0021,  0.0115])\n",
      "\tparams: tensor([  5.3558, -17.2371])\n",
      "Epoch: 3269,Loss: 2.928047\n",
      "\tgrad: tensor([-0.0020,  0.0115])\n",
      "\tparams: tensor([  5.3558, -17.2372])\n",
      "Epoch: 3270,Loss: 2.928046\n",
      "\tgrad: tensor([-0.0020,  0.0115])\n",
      "\tparams: tensor([  5.3558, -17.2373])\n",
      "Epoch: 3271,Loss: 2.928046\n",
      "\tgrad: tensor([-0.0020,  0.0115])\n",
      "\tparams: tensor([  5.3558, -17.2374])\n",
      "Epoch: 3272,Loss: 2.928044\n",
      "\tgrad: tensor([-0.0020,  0.0115])\n",
      "\tparams: tensor([  5.3558, -17.2375])\n",
      "Epoch: 3273,Loss: 2.928042\n",
      "\tgrad: tensor([-0.0020,  0.0114])\n",
      "\tparams: tensor([  5.3559, -17.2376])\n",
      "Epoch: 3274,Loss: 2.928040\n",
      "\tgrad: tensor([-0.0020,  0.0114])\n",
      "\tparams: tensor([  5.3559, -17.2377])\n",
      "Epoch: 3275,Loss: 2.928040\n",
      "\tgrad: tensor([-0.0020,  0.0114])\n",
      "\tparams: tensor([  5.3559, -17.2379])\n",
      "Epoch: 3276,Loss: 2.928036\n",
      "\tgrad: tensor([-0.0020,  0.0114])\n",
      "\tparams: tensor([  5.3559, -17.2380])\n",
      "Epoch: 3277,Loss: 2.928036\n",
      "\tgrad: tensor([-0.0020,  0.0113])\n",
      "\tparams: tensor([  5.3559, -17.2381])\n",
      "Epoch: 3278,Loss: 2.928037\n",
      "\tgrad: tensor([-0.0020,  0.0113])\n",
      "\tparams: tensor([  5.3560, -17.2382])\n",
      "Epoch: 3279,Loss: 2.928034\n",
      "\tgrad: tensor([-0.0020,  0.0113])\n",
      "\tparams: tensor([  5.3560, -17.2383])\n",
      "Epoch: 3280,Loss: 2.928034\n",
      "\tgrad: tensor([-0.0020,  0.0113])\n",
      "\tparams: tensor([  5.3560, -17.2384])\n",
      "Epoch: 3281,Loss: 2.928031\n",
      "\tgrad: tensor([-0.0020,  0.0113])\n",
      "\tparams: tensor([  5.3560, -17.2385])\n",
      "Epoch: 3282,Loss: 2.928032\n",
      "\tgrad: tensor([-0.0020,  0.0113])\n",
      "\tparams: tensor([  5.3560, -17.2386])\n",
      "Epoch: 3283,Loss: 2.928028\n",
      "\tgrad: tensor([-0.0020,  0.0112])\n",
      "\tparams: tensor([  5.3561, -17.2388])\n",
      "Epoch: 3284,Loss: 2.928027\n",
      "\tgrad: tensor([-0.0020,  0.0112])\n",
      "\tparams: tensor([  5.3561, -17.2389])\n",
      "Epoch: 3285,Loss: 2.928026\n",
      "\tgrad: tensor([-0.0020,  0.0112])\n",
      "\tparams: tensor([  5.3561, -17.2390])\n",
      "Epoch: 3286,Loss: 2.928025\n",
      "\tgrad: tensor([-0.0020,  0.0112])\n",
      "\tparams: tensor([  5.3561, -17.2391])\n",
      "Epoch: 3287,Loss: 2.928024\n",
      "\tgrad: tensor([-0.0020,  0.0112])\n",
      "\tparams: tensor([  5.3561, -17.2392])\n",
      "Epoch: 3288,Loss: 2.928022\n",
      "\tgrad: tensor([-0.0020,  0.0111])\n",
      "\tparams: tensor([  5.3562, -17.2393])\n",
      "Epoch: 3289,Loss: 2.928023\n",
      "\tgrad: tensor([-0.0020,  0.0111])\n",
      "\tparams: tensor([  5.3562, -17.2394])\n",
      "Epoch: 3290,Loss: 2.928021\n",
      "\tgrad: tensor([-0.0020,  0.0111])\n",
      "\tparams: tensor([  5.3562, -17.2395])\n",
      "Epoch: 3291,Loss: 2.928019\n",
      "\tgrad: tensor([-0.0020,  0.0111])\n",
      "\tparams: tensor([  5.3562, -17.2397])\n",
      "Epoch: 3292,Loss: 2.928018\n",
      "\tgrad: tensor([-0.0020,  0.0111])\n",
      "\tparams: tensor([  5.3562, -17.2398])\n",
      "Epoch: 3293,Loss: 2.928017\n",
      "\tgrad: tensor([-0.0020,  0.0110])\n",
      "\tparams: tensor([  5.3563, -17.2399])\n",
      "Epoch: 3294,Loss: 2.928015\n",
      "\tgrad: tensor([-0.0020,  0.0110])\n",
      "\tparams: tensor([  5.3563, -17.2400])\n",
      "Epoch: 3295,Loss: 2.928013\n",
      "\tgrad: tensor([-0.0020,  0.0110])\n",
      "\tparams: tensor([  5.3563, -17.2401])\n",
      "Epoch: 3296,Loss: 2.928013\n",
      "\tgrad: tensor([-0.0019,  0.0110])\n",
      "\tparams: tensor([  5.3563, -17.2402])\n",
      "Epoch: 3297,Loss: 2.928011\n",
      "\tgrad: tensor([-0.0019,  0.0110])\n",
      "\tparams: tensor([  5.3563, -17.2403])\n",
      "Epoch: 3298,Loss: 2.928009\n",
      "\tgrad: tensor([-0.0019,  0.0110])\n",
      "\tparams: tensor([  5.3563, -17.2404])\n",
      "Epoch: 3299,Loss: 2.928008\n",
      "\tgrad: tensor([-0.0019,  0.0109])\n",
      "\tparams: tensor([  5.3564, -17.2405])\n",
      "Epoch: 3300,Loss: 2.928006\n",
      "\tgrad: tensor([-0.0019,  0.0109])\n",
      "\tparams: tensor([  5.3564, -17.2406])\n",
      "Epoch: 3301,Loss: 2.928007\n",
      "\tgrad: tensor([-0.0019,  0.0109])\n",
      "\tparams: tensor([  5.3564, -17.2407])\n",
      "Epoch: 3302,Loss: 2.928007\n",
      "\tgrad: tensor([-0.0019,  0.0109])\n",
      "\tparams: tensor([  5.3564, -17.2409])\n",
      "Epoch: 3303,Loss: 2.928004\n",
      "\tgrad: tensor([-0.0019,  0.0109])\n",
      "\tparams: tensor([  5.3564, -17.2410])\n",
      "Epoch: 3304,Loss: 2.928002\n",
      "\tgrad: tensor([-0.0019,  0.0108])\n",
      "\tparams: tensor([  5.3565, -17.2411])\n",
      "Epoch: 3305,Loss: 2.928002\n",
      "\tgrad: tensor([-0.0019,  0.0108])\n",
      "\tparams: tensor([  5.3565, -17.2412])\n",
      "Epoch: 3306,Loss: 2.928000\n",
      "\tgrad: tensor([-0.0019,  0.0108])\n",
      "\tparams: tensor([  5.3565, -17.2413])\n",
      "Epoch: 3307,Loss: 2.928000\n",
      "\tgrad: tensor([-0.0019,  0.0108])\n",
      "\tparams: tensor([  5.3565, -17.2414])\n",
      "Epoch: 3308,Loss: 2.927998\n",
      "\tgrad: tensor([-0.0019,  0.0108])\n",
      "\tparams: tensor([  5.3565, -17.2415])\n",
      "Epoch: 3309,Loss: 2.927995\n",
      "\tgrad: tensor([-0.0019,  0.0107])\n",
      "\tparams: tensor([  5.3566, -17.2416])\n",
      "Epoch: 3310,Loss: 2.927995\n",
      "\tgrad: tensor([-0.0019,  0.0107])\n",
      "\tparams: tensor([  5.3566, -17.2417])\n",
      "Epoch: 3311,Loss: 2.927994\n",
      "\tgrad: tensor([-0.0019,  0.0107])\n",
      "\tparams: tensor([  5.3566, -17.2418])\n",
      "Epoch: 3312,Loss: 2.927994\n",
      "\tgrad: tensor([-0.0019,  0.0107])\n",
      "\tparams: tensor([  5.3566, -17.2419])\n",
      "Epoch: 3313,Loss: 2.927991\n",
      "\tgrad: tensor([-0.0019,  0.0107])\n",
      "\tparams: tensor([  5.3566, -17.2420])\n",
      "Epoch: 3314,Loss: 2.927991\n",
      "\tgrad: tensor([-0.0019,  0.0107])\n",
      "\tparams: tensor([  5.3567, -17.2421])\n",
      "Epoch: 3315,Loss: 2.927990\n",
      "\tgrad: tensor([-0.0019,  0.0106])\n",
      "\tparams: tensor([  5.3567, -17.2423])\n",
      "Epoch: 3316,Loss: 2.927989\n",
      "\tgrad: tensor([-0.0019,  0.0106])\n",
      "\tparams: tensor([  5.3567, -17.2424])\n",
      "Epoch: 3317,Loss: 2.927988\n",
      "\tgrad: tensor([-0.0019,  0.0106])\n",
      "\tparams: tensor([  5.3567, -17.2425])\n",
      "Epoch: 3318,Loss: 2.927986\n",
      "\tgrad: tensor([-0.0019,  0.0106])\n",
      "\tparams: tensor([  5.3567, -17.2426])\n",
      "Epoch: 3319,Loss: 2.927985\n",
      "\tgrad: tensor([-0.0019,  0.0106])\n",
      "\tparams: tensor([  5.3567, -17.2427])\n",
      "Epoch: 3320,Loss: 2.927983\n",
      "\tgrad: tensor([-0.0018,  0.0106])\n",
      "\tparams: tensor([  5.3568, -17.2428])\n",
      "Epoch: 3321,Loss: 2.927983\n",
      "\tgrad: tensor([-0.0018,  0.0105])\n",
      "\tparams: tensor([  5.3568, -17.2429])\n",
      "Epoch: 3322,Loss: 2.927981\n",
      "\tgrad: tensor([-0.0018,  0.0105])\n",
      "\tparams: tensor([  5.3568, -17.2430])\n",
      "Epoch: 3323,Loss: 2.927980\n",
      "\tgrad: tensor([-0.0018,  0.0105])\n",
      "\tparams: tensor([  5.3568, -17.2431])\n",
      "Epoch: 3324,Loss: 2.927979\n",
      "\tgrad: tensor([-0.0018,  0.0105])\n",
      "\tparams: tensor([  5.3568, -17.2432])\n",
      "Epoch: 3325,Loss: 2.927979\n",
      "\tgrad: tensor([-0.0018,  0.0105])\n",
      "\tparams: tensor([  5.3569, -17.2433])\n",
      "Epoch: 3326,Loss: 2.927977\n",
      "\tgrad: tensor([-0.0018,  0.0104])\n",
      "\tparams: tensor([  5.3569, -17.2434])\n",
      "Epoch: 3327,Loss: 2.927975\n",
      "\tgrad: tensor([-0.0019,  0.0104])\n",
      "\tparams: tensor([  5.3569, -17.2435])\n",
      "Epoch: 3328,Loss: 2.927973\n",
      "\tgrad: tensor([-0.0018,  0.0104])\n",
      "\tparams: tensor([  5.3569, -17.2436])\n",
      "Epoch: 3329,Loss: 2.927974\n",
      "\tgrad: tensor([-0.0018,  0.0104])\n",
      "\tparams: tensor([  5.3569, -17.2437])\n",
      "Epoch: 3330,Loss: 2.927974\n",
      "\tgrad: tensor([-0.0018,  0.0104])\n",
      "\tparams: tensor([  5.3570, -17.2438])\n",
      "Epoch: 3331,Loss: 2.927972\n",
      "\tgrad: tensor([-0.0018,  0.0104])\n",
      "\tparams: tensor([  5.3570, -17.2439])\n",
      "Epoch: 3332,Loss: 2.927972\n",
      "\tgrad: tensor([-0.0018,  0.0103])\n",
      "\tparams: tensor([  5.3570, -17.2440])\n",
      "Epoch: 3333,Loss: 2.927969\n",
      "\tgrad: tensor([-0.0018,  0.0103])\n",
      "\tparams: tensor([  5.3570, -17.2441])\n",
      "Epoch: 3334,Loss: 2.927969\n",
      "\tgrad: tensor([-0.0018,  0.0103])\n",
      "\tparams: tensor([  5.3570, -17.2442])\n",
      "Epoch: 3335,Loss: 2.927967\n",
      "\tgrad: tensor([-0.0018,  0.0103])\n",
      "\tparams: tensor([  5.3570, -17.2443])\n",
      "Epoch: 3336,Loss: 2.927967\n",
      "\tgrad: tensor([-0.0018,  0.0103])\n",
      "\tparams: tensor([  5.3571, -17.2444])\n",
      "Epoch: 3337,Loss: 2.927963\n",
      "\tgrad: tensor([-0.0018,  0.0102])\n",
      "\tparams: tensor([  5.3571, -17.2446])\n",
      "Epoch: 3338,Loss: 2.927963\n",
      "\tgrad: tensor([-0.0018,  0.0102])\n",
      "\tparams: tensor([  5.3571, -17.2447])\n",
      "Epoch: 3339,Loss: 2.927962\n",
      "\tgrad: tensor([-0.0018,  0.0102])\n",
      "\tparams: tensor([  5.3571, -17.2448])\n",
      "Epoch: 3340,Loss: 2.927962\n",
      "\tgrad: tensor([-0.0018,  0.0102])\n",
      "\tparams: tensor([  5.3571, -17.2449])\n",
      "Epoch: 3341,Loss: 2.927960\n",
      "\tgrad: tensor([-0.0018,  0.0102])\n",
      "\tparams: tensor([  5.3572, -17.2450])\n",
      "Epoch: 3342,Loss: 2.927960\n",
      "\tgrad: tensor([-0.0018,  0.0102])\n",
      "\tparams: tensor([  5.3572, -17.2451])\n",
      "Epoch: 3343,Loss: 2.927959\n",
      "\tgrad: tensor([-0.0018,  0.0101])\n",
      "\tparams: tensor([  5.3572, -17.2452])\n",
      "Epoch: 3344,Loss: 2.927958\n",
      "\tgrad: tensor([-0.0018,  0.0101])\n",
      "\tparams: tensor([  5.3572, -17.2453])\n",
      "Epoch: 3345,Loss: 2.927956\n",
      "\tgrad: tensor([-0.0018,  0.0101])\n",
      "\tparams: tensor([  5.3572, -17.2454])\n",
      "Epoch: 3346,Loss: 2.927956\n",
      "\tgrad: tensor([-0.0018,  0.0101])\n",
      "\tparams: tensor([  5.3572, -17.2455])\n",
      "Epoch: 3347,Loss: 2.927955\n",
      "\tgrad: tensor([-0.0018,  0.0101])\n",
      "\tparams: tensor([  5.3573, -17.2456])\n",
      "Epoch: 3348,Loss: 2.927953\n",
      "\tgrad: tensor([-0.0018,  0.0101])\n",
      "\tparams: tensor([  5.3573, -17.2457])\n",
      "Epoch: 3349,Loss: 2.927953\n",
      "\tgrad: tensor([-0.0018,  0.0100])\n",
      "\tparams: tensor([  5.3573, -17.2458])\n",
      "Epoch: 3350,Loss: 2.927951\n",
      "\tgrad: tensor([-0.0018,  0.0100])\n",
      "\tparams: tensor([  5.3573, -17.2459])\n",
      "Epoch: 3351,Loss: 2.927950\n",
      "\tgrad: tensor([-0.0018,  0.0100])\n",
      "\tparams: tensor([  5.3573, -17.2460])\n",
      "Epoch: 3352,Loss: 2.927948\n",
      "\tgrad: tensor([-0.0018,  0.0100])\n",
      "\tparams: tensor([  5.3573, -17.2461])\n",
      "Epoch: 3353,Loss: 2.927947\n",
      "\tgrad: tensor([-0.0017,  0.0100])\n",
      "\tparams: tensor([  5.3574, -17.2462])\n",
      "Epoch: 3354,Loss: 2.927948\n",
      "\tgrad: tensor([-0.0018,  0.0100])\n",
      "\tparams: tensor([  5.3574, -17.2463])\n",
      "Epoch: 3355,Loss: 2.927945\n",
      "\tgrad: tensor([-0.0017,  0.0099])\n",
      "\tparams: tensor([  5.3574, -17.2464])\n",
      "Epoch: 3356,Loss: 2.927944\n",
      "\tgrad: tensor([-0.0017,  0.0099])\n",
      "\tparams: tensor([  5.3574, -17.2465])\n",
      "Epoch: 3357,Loss: 2.927943\n",
      "\tgrad: tensor([-0.0018,  0.0099])\n",
      "\tparams: tensor([  5.3574, -17.2466])\n",
      "Epoch: 3358,Loss: 2.927944\n",
      "\tgrad: tensor([-0.0017,  0.0099])\n",
      "\tparams: tensor([  5.3575, -17.2467])\n",
      "Epoch: 3359,Loss: 2.927942\n",
      "\tgrad: tensor([-0.0017,  0.0099])\n",
      "\tparams: tensor([  5.3575, -17.2468])\n",
      "Epoch: 3360,Loss: 2.927941\n",
      "\tgrad: tensor([-0.0018,  0.0099])\n",
      "\tparams: tensor([  5.3575, -17.2469])\n",
      "Epoch: 3361,Loss: 2.927940\n",
      "\tgrad: tensor([-0.0017,  0.0098])\n",
      "\tparams: tensor([  5.3575, -17.2470])\n",
      "Epoch: 3362,Loss: 2.927938\n",
      "\tgrad: tensor([-0.0017,  0.0098])\n",
      "\tparams: tensor([  5.3575, -17.2471])\n",
      "Epoch: 3363,Loss: 2.927938\n",
      "\tgrad: tensor([-0.0018,  0.0098])\n",
      "\tparams: tensor([  5.3575, -17.2472])\n",
      "Epoch: 3364,Loss: 2.927936\n",
      "\tgrad: tensor([-0.0017,  0.0098])\n",
      "\tparams: tensor([  5.3576, -17.2473])\n",
      "Epoch: 3365,Loss: 2.927936\n",
      "\tgrad: tensor([-0.0017,  0.0098])\n",
      "\tparams: tensor([  5.3576, -17.2474])\n",
      "Epoch: 3366,Loss: 2.927937\n",
      "\tgrad: tensor([-0.0017,  0.0098])\n",
      "\tparams: tensor([  5.3576, -17.2474])\n",
      "Epoch: 3367,Loss: 2.927934\n",
      "\tgrad: tensor([-0.0017,  0.0097])\n",
      "\tparams: tensor([  5.3576, -17.2475])\n",
      "Epoch: 3368,Loss: 2.927933\n",
      "\tgrad: tensor([-0.0017,  0.0097])\n",
      "\tparams: tensor([  5.3576, -17.2476])\n",
      "Epoch: 3369,Loss: 2.927932\n",
      "\tgrad: tensor([-0.0017,  0.0097])\n",
      "\tparams: tensor([  5.3576, -17.2477])\n",
      "Epoch: 3370,Loss: 2.927930\n",
      "\tgrad: tensor([-0.0017,  0.0097])\n",
      "\tparams: tensor([  5.3577, -17.2478])\n",
      "Epoch: 3371,Loss: 2.927928\n",
      "\tgrad: tensor([-0.0017,  0.0097])\n",
      "\tparams: tensor([  5.3577, -17.2479])\n",
      "Epoch: 3372,Loss: 2.927931\n",
      "\tgrad: tensor([-0.0017,  0.0097])\n",
      "\tparams: tensor([  5.3577, -17.2480])\n",
      "Epoch: 3373,Loss: 2.927929\n",
      "\tgrad: tensor([-0.0017,  0.0096])\n",
      "\tparams: tensor([  5.3577, -17.2481])\n",
      "Epoch: 3374,Loss: 2.927927\n",
      "\tgrad: tensor([-0.0017,  0.0096])\n",
      "\tparams: tensor([  5.3577, -17.2482])\n",
      "Epoch: 3375,Loss: 2.927926\n",
      "\tgrad: tensor([-0.0017,  0.0096])\n",
      "\tparams: tensor([  5.3577, -17.2483])\n",
      "Epoch: 3376,Loss: 2.927925\n",
      "\tgrad: tensor([-0.0017,  0.0096])\n",
      "\tparams: tensor([  5.3578, -17.2484])\n",
      "Epoch: 3377,Loss: 2.927924\n",
      "\tgrad: tensor([-0.0017,  0.0096])\n",
      "\tparams: tensor([  5.3578, -17.2485])\n",
      "Epoch: 3378,Loss: 2.927923\n",
      "\tgrad: tensor([-0.0017,  0.0096])\n",
      "\tparams: tensor([  5.3578, -17.2486])\n",
      "Epoch: 3379,Loss: 2.927924\n",
      "\tgrad: tensor([-0.0017,  0.0095])\n",
      "\tparams: tensor([  5.3578, -17.2487])\n",
      "Epoch: 3380,Loss: 2.927922\n",
      "\tgrad: tensor([-0.0017,  0.0095])\n",
      "\tparams: tensor([  5.3578, -17.2488])\n",
      "Epoch: 3381,Loss: 2.927922\n",
      "\tgrad: tensor([-0.0017,  0.0095])\n",
      "\tparams: tensor([  5.3578, -17.2489])\n",
      "Epoch: 3382,Loss: 2.927920\n",
      "\tgrad: tensor([-0.0017,  0.0095])\n",
      "\tparams: tensor([  5.3579, -17.2490])\n",
      "Epoch: 3383,Loss: 2.927918\n",
      "\tgrad: tensor([-0.0017,  0.0095])\n",
      "\tparams: tensor([  5.3579, -17.2491])\n",
      "Epoch: 3384,Loss: 2.927917\n",
      "\tgrad: tensor([-0.0017,  0.0095])\n",
      "\tparams: tensor([  5.3579, -17.2492])\n",
      "Epoch: 3385,Loss: 2.927917\n",
      "\tgrad: tensor([-0.0017,  0.0094])\n",
      "\tparams: tensor([  5.3579, -17.2493])\n",
      "Epoch: 3386,Loss: 2.927915\n",
      "\tgrad: tensor([-0.0017,  0.0094])\n",
      "\tparams: tensor([  5.3579, -17.2494])\n",
      "Epoch: 3387,Loss: 2.927915\n",
      "\tgrad: tensor([-0.0017,  0.0094])\n",
      "\tparams: tensor([  5.3579, -17.2495])\n",
      "Epoch: 3388,Loss: 2.927914\n",
      "\tgrad: tensor([-0.0016,  0.0094])\n",
      "\tparams: tensor([  5.3580, -17.2496])\n",
      "Epoch: 3389,Loss: 2.927913\n",
      "\tgrad: tensor([-0.0017,  0.0094])\n",
      "\tparams: tensor([  5.3580, -17.2496])\n",
      "Epoch: 3390,Loss: 2.927911\n",
      "\tgrad: tensor([-0.0016,  0.0094])\n",
      "\tparams: tensor([  5.3580, -17.2497])\n",
      "Epoch: 3391,Loss: 2.927913\n",
      "\tgrad: tensor([-0.0017,  0.0093])\n",
      "\tparams: tensor([  5.3580, -17.2498])\n",
      "Epoch: 3392,Loss: 2.927911\n",
      "\tgrad: tensor([-0.0016,  0.0093])\n",
      "\tparams: tensor([  5.3580, -17.2499])\n",
      "Epoch: 3393,Loss: 2.927910\n",
      "\tgrad: tensor([-0.0016,  0.0093])\n",
      "\tparams: tensor([  5.3580, -17.2500])\n",
      "Epoch: 3394,Loss: 2.927909\n",
      "\tgrad: tensor([-0.0016,  0.0093])\n",
      "\tparams: tensor([  5.3581, -17.2501])\n",
      "Epoch: 3395,Loss: 2.927908\n",
      "\tgrad: tensor([-0.0016,  0.0093])\n",
      "\tparams: tensor([  5.3581, -17.2502])\n",
      "Epoch: 3396,Loss: 2.927907\n",
      "\tgrad: tensor([-0.0017,  0.0093])\n",
      "\tparams: tensor([  5.3581, -17.2503])\n",
      "Epoch: 3397,Loss: 2.927906\n",
      "\tgrad: tensor([-0.0016,  0.0093])\n",
      "\tparams: tensor([  5.3581, -17.2504])\n",
      "Epoch: 3398,Loss: 2.927905\n",
      "\tgrad: tensor([-0.0017,  0.0092])\n",
      "\tparams: tensor([  5.3581, -17.2505])\n",
      "Epoch: 3399,Loss: 2.927905\n",
      "\tgrad: tensor([-0.0016,  0.0092])\n",
      "\tparams: tensor([  5.3581, -17.2506])\n",
      "Epoch: 3400,Loss: 2.927904\n",
      "\tgrad: tensor([-0.0016,  0.0092])\n",
      "\tparams: tensor([  5.3582, -17.2507])\n",
      "Epoch: 3401,Loss: 2.927902\n",
      "\tgrad: tensor([-0.0016,  0.0092])\n",
      "\tparams: tensor([  5.3582, -17.2508])\n",
      "Epoch: 3402,Loss: 2.927902\n",
      "\tgrad: tensor([-0.0016,  0.0092])\n",
      "\tparams: tensor([  5.3582, -17.2509])\n",
      "Epoch: 3403,Loss: 2.927902\n",
      "\tgrad: tensor([-0.0016,  0.0092])\n",
      "\tparams: tensor([  5.3582, -17.2509])\n",
      "Epoch: 3404,Loss: 2.927899\n",
      "\tgrad: tensor([-0.0016,  0.0091])\n",
      "\tparams: tensor([  5.3582, -17.2510])\n",
      "Epoch: 3405,Loss: 2.927899\n",
      "\tgrad: tensor([-0.0016,  0.0091])\n",
      "\tparams: tensor([  5.3582, -17.2511])\n",
      "Epoch: 3406,Loss: 2.927898\n",
      "\tgrad: tensor([-0.0016,  0.0091])\n",
      "\tparams: tensor([  5.3583, -17.2512])\n",
      "Epoch: 3407,Loss: 2.927899\n",
      "\tgrad: tensor([-0.0016,  0.0091])\n",
      "\tparams: tensor([  5.3583, -17.2513])\n",
      "Epoch: 3408,Loss: 2.927896\n",
      "\tgrad: tensor([-0.0016,  0.0091])\n",
      "\tparams: tensor([  5.3583, -17.2514])\n",
      "Epoch: 3409,Loss: 2.927895\n",
      "\tgrad: tensor([-0.0016,  0.0091])\n",
      "\tparams: tensor([  5.3583, -17.2515])\n",
      "Epoch: 3410,Loss: 2.927896\n",
      "\tgrad: tensor([-0.0016,  0.0091])\n",
      "\tparams: tensor([  5.3583, -17.2516])\n",
      "Epoch: 3411,Loss: 2.927894\n",
      "\tgrad: tensor([-0.0016,  0.0090])\n",
      "\tparams: tensor([  5.3583, -17.2517])\n",
      "Epoch: 3412,Loss: 2.927892\n",
      "\tgrad: tensor([-0.0016,  0.0090])\n",
      "\tparams: tensor([  5.3584, -17.2518])\n",
      "Epoch: 3413,Loss: 2.927892\n",
      "\tgrad: tensor([-0.0016,  0.0090])\n",
      "\tparams: tensor([  5.3584, -17.2519])\n",
      "Epoch: 3414,Loss: 2.927891\n",
      "\tgrad: tensor([-0.0016,  0.0090])\n",
      "\tparams: tensor([  5.3584, -17.2519])\n",
      "Epoch: 3415,Loss: 2.927891\n",
      "\tgrad: tensor([-0.0016,  0.0090])\n",
      "\tparams: tensor([  5.3584, -17.2520])\n",
      "Epoch: 3416,Loss: 2.927890\n",
      "\tgrad: tensor([-0.0016,  0.0090])\n",
      "\tparams: tensor([  5.3584, -17.2521])\n",
      "Epoch: 3417,Loss: 2.927891\n",
      "\tgrad: tensor([-0.0016,  0.0089])\n",
      "\tparams: tensor([  5.3584, -17.2522])\n",
      "Epoch: 3418,Loss: 2.927888\n",
      "\tgrad: tensor([-0.0016,  0.0089])\n",
      "\tparams: tensor([  5.3584, -17.2523])\n",
      "Epoch: 3419,Loss: 2.927888\n",
      "\tgrad: tensor([-0.0016,  0.0089])\n",
      "\tparams: tensor([  5.3585, -17.2524])\n",
      "Epoch: 3420,Loss: 2.927886\n",
      "\tgrad: tensor([-0.0016,  0.0089])\n",
      "\tparams: tensor([  5.3585, -17.2525])\n",
      "Epoch: 3421,Loss: 2.927887\n",
      "\tgrad: tensor([-0.0016,  0.0089])\n",
      "\tparams: tensor([  5.3585, -17.2526])\n",
      "Epoch: 3422,Loss: 2.927886\n",
      "\tgrad: tensor([-0.0016,  0.0089])\n",
      "\tparams: tensor([  5.3585, -17.2527])\n",
      "Epoch: 3423,Loss: 2.927884\n",
      "\tgrad: tensor([-0.0016,  0.0089])\n",
      "\tparams: tensor([  5.3585, -17.2527])\n",
      "Epoch: 3424,Loss: 2.927883\n",
      "\tgrad: tensor([-0.0015,  0.0088])\n",
      "\tparams: tensor([  5.3585, -17.2528])\n",
      "Epoch: 3425,Loss: 2.927881\n",
      "\tgrad: tensor([-0.0015,  0.0088])\n",
      "\tparams: tensor([  5.3586, -17.2529])\n",
      "Epoch: 3426,Loss: 2.927881\n",
      "\tgrad: tensor([-0.0016,  0.0088])\n",
      "\tparams: tensor([  5.3586, -17.2530])\n",
      "Epoch: 3427,Loss: 2.927880\n",
      "\tgrad: tensor([-0.0015,  0.0088])\n",
      "\tparams: tensor([  5.3586, -17.2531])\n",
      "Epoch: 3428,Loss: 2.927880\n",
      "\tgrad: tensor([-0.0016,  0.0088])\n",
      "\tparams: tensor([  5.3586, -17.2532])\n",
      "Epoch: 3429,Loss: 2.927879\n",
      "\tgrad: tensor([-0.0015,  0.0088])\n",
      "\tparams: tensor([  5.3586, -17.2533])\n",
      "Epoch: 3430,Loss: 2.927877\n",
      "\tgrad: tensor([-0.0016,  0.0087])\n",
      "\tparams: tensor([  5.3586, -17.2534])\n",
      "Epoch: 3431,Loss: 2.927876\n",
      "\tgrad: tensor([-0.0015,  0.0087])\n",
      "\tparams: tensor([  5.3586, -17.2534])\n",
      "Epoch: 3432,Loss: 2.927876\n",
      "\tgrad: tensor([-0.0015,  0.0087])\n",
      "\tparams: tensor([  5.3587, -17.2535])\n",
      "Epoch: 3433,Loss: 2.927876\n",
      "\tgrad: tensor([-0.0015,  0.0087])\n",
      "\tparams: tensor([  5.3587, -17.2536])\n",
      "Epoch: 3434,Loss: 2.927876\n",
      "\tgrad: tensor([-0.0016,  0.0087])\n",
      "\tparams: tensor([  5.3587, -17.2537])\n",
      "Epoch: 3435,Loss: 2.927876\n",
      "\tgrad: tensor([-0.0016,  0.0087])\n",
      "\tparams: tensor([  5.3587, -17.2538])\n",
      "Epoch: 3436,Loss: 2.927875\n",
      "\tgrad: tensor([-0.0015,  0.0087])\n",
      "\tparams: tensor([  5.3587, -17.2539])\n",
      "Epoch: 3437,Loss: 2.927873\n",
      "\tgrad: tensor([-0.0015,  0.0087])\n",
      "\tparams: tensor([  5.3587, -17.2540])\n",
      "Epoch: 3438,Loss: 2.927872\n",
      "\tgrad: tensor([-0.0015,  0.0086])\n",
      "\tparams: tensor([  5.3588, -17.2541])\n",
      "Epoch: 3439,Loss: 2.927871\n",
      "\tgrad: tensor([-0.0015,  0.0086])\n",
      "\tparams: tensor([  5.3588, -17.2541])\n",
      "Epoch: 3440,Loss: 2.927870\n",
      "\tgrad: tensor([-0.0015,  0.0086])\n",
      "\tparams: tensor([  5.3588, -17.2542])\n",
      "Epoch: 3441,Loss: 2.927871\n",
      "\tgrad: tensor([-0.0015,  0.0086])\n",
      "\tparams: tensor([  5.3588, -17.2543])\n",
      "Epoch: 3442,Loss: 2.927869\n",
      "\tgrad: tensor([-0.0015,  0.0086])\n",
      "\tparams: tensor([  5.3588, -17.2544])\n",
      "Epoch: 3443,Loss: 2.927869\n",
      "\tgrad: tensor([-0.0015,  0.0086])\n",
      "\tparams: tensor([  5.3588, -17.2545])\n",
      "Epoch: 3444,Loss: 2.927867\n",
      "\tgrad: tensor([-0.0015,  0.0085])\n",
      "\tparams: tensor([  5.3588, -17.2546])\n",
      "Epoch: 3445,Loss: 2.927866\n",
      "\tgrad: tensor([-0.0015,  0.0085])\n",
      "\tparams: tensor([  5.3589, -17.2547])\n",
      "Epoch: 3446,Loss: 2.927866\n",
      "\tgrad: tensor([-0.0015,  0.0085])\n",
      "\tparams: tensor([  5.3589, -17.2547])\n",
      "Epoch: 3447,Loss: 2.927866\n",
      "\tgrad: tensor([-0.0015,  0.0085])\n",
      "\tparams: tensor([  5.3589, -17.2548])\n",
      "Epoch: 3448,Loss: 2.927864\n",
      "\tgrad: tensor([-0.0015,  0.0085])\n",
      "\tparams: tensor([  5.3589, -17.2549])\n",
      "Epoch: 3449,Loss: 2.927863\n",
      "\tgrad: tensor([-0.0015,  0.0085])\n",
      "\tparams: tensor([  5.3589, -17.2550])\n",
      "Epoch: 3450,Loss: 2.927863\n",
      "\tgrad: tensor([-0.0015,  0.0085])\n",
      "\tparams: tensor([  5.3589, -17.2551])\n",
      "Epoch: 3451,Loss: 2.927862\n",
      "\tgrad: tensor([-0.0015,  0.0084])\n",
      "\tparams: tensor([  5.3590, -17.2552])\n",
      "Epoch: 3452,Loss: 2.927863\n",
      "\tgrad: tensor([-0.0015,  0.0084])\n",
      "\tparams: tensor([  5.3590, -17.2552])\n",
      "Epoch: 3453,Loss: 2.927860\n",
      "\tgrad: tensor([-0.0015,  0.0084])\n",
      "\tparams: tensor([  5.3590, -17.2553])\n",
      "Epoch: 3454,Loss: 2.927860\n",
      "\tgrad: tensor([-0.0015,  0.0084])\n",
      "\tparams: tensor([  5.3590, -17.2554])\n",
      "Epoch: 3455,Loss: 2.927860\n",
      "\tgrad: tensor([-0.0015,  0.0084])\n",
      "\tparams: tensor([  5.3590, -17.2555])\n",
      "Epoch: 3456,Loss: 2.927859\n",
      "\tgrad: tensor([-0.0015,  0.0084])\n",
      "\tparams: tensor([  5.3590, -17.2556])\n",
      "Epoch: 3457,Loss: 2.927858\n",
      "\tgrad: tensor([-0.0015,  0.0084])\n",
      "\tparams: tensor([  5.3590, -17.2557])\n",
      "Epoch: 3458,Loss: 2.927858\n",
      "\tgrad: tensor([-0.0015,  0.0083])\n",
      "\tparams: tensor([  5.3591, -17.2557])\n",
      "Epoch: 3459,Loss: 2.927856\n",
      "\tgrad: tensor([-0.0015,  0.0083])\n",
      "\tparams: tensor([  5.3591, -17.2558])\n",
      "Epoch: 3460,Loss: 2.927857\n",
      "\tgrad: tensor([-0.0015,  0.0083])\n",
      "\tparams: tensor([  5.3591, -17.2559])\n",
      "Epoch: 3461,Loss: 2.927854\n",
      "\tgrad: tensor([-0.0015,  0.0083])\n",
      "\tparams: tensor([  5.3591, -17.2560])\n",
      "Epoch: 3462,Loss: 2.927855\n",
      "\tgrad: tensor([-0.0015,  0.0083])\n",
      "\tparams: tensor([  5.3591, -17.2561])\n",
      "Epoch: 3463,Loss: 2.927854\n",
      "\tgrad: tensor([-0.0015,  0.0083])\n",
      "\tparams: tensor([  5.3591, -17.2562])\n",
      "Epoch: 3464,Loss: 2.927854\n",
      "\tgrad: tensor([-0.0015,  0.0083])\n",
      "\tparams: tensor([  5.3591, -17.2562])\n",
      "Epoch: 3465,Loss: 2.927851\n",
      "\tgrad: tensor([-0.0014,  0.0082])\n",
      "\tparams: tensor([  5.3592, -17.2563])\n",
      "Epoch: 3466,Loss: 2.927853\n",
      "\tgrad: tensor([-0.0015,  0.0082])\n",
      "\tparams: tensor([  5.3592, -17.2564])\n",
      "Epoch: 3467,Loss: 2.927852\n",
      "\tgrad: tensor([-0.0014,  0.0082])\n",
      "\tparams: tensor([  5.3592, -17.2565])\n",
      "Epoch: 3468,Loss: 2.927850\n",
      "\tgrad: tensor([-0.0014,  0.0082])\n",
      "\tparams: tensor([  5.3592, -17.2566])\n",
      "Epoch: 3469,Loss: 2.927849\n",
      "\tgrad: tensor([-0.0015,  0.0082])\n",
      "\tparams: tensor([  5.3592, -17.2567])\n",
      "Epoch: 3470,Loss: 2.927849\n",
      "\tgrad: tensor([-0.0015,  0.0082])\n",
      "\tparams: tensor([  5.3592, -17.2567])\n",
      "Epoch: 3471,Loss: 2.927848\n",
      "\tgrad: tensor([-0.0014,  0.0082])\n",
      "\tparams: tensor([  5.3592, -17.2568])\n",
      "Epoch: 3472,Loss: 2.927848\n",
      "\tgrad: tensor([-0.0014,  0.0081])\n",
      "\tparams: tensor([  5.3593, -17.2569])\n",
      "Epoch: 3473,Loss: 2.927846\n",
      "\tgrad: tensor([-0.0015,  0.0081])\n",
      "\tparams: tensor([  5.3593, -17.2570])\n",
      "Epoch: 3474,Loss: 2.927846\n",
      "\tgrad: tensor([-0.0015,  0.0081])\n",
      "\tparams: tensor([  5.3593, -17.2571])\n",
      "Epoch: 3475,Loss: 2.927845\n",
      "\tgrad: tensor([-0.0014,  0.0081])\n",
      "\tparams: tensor([  5.3593, -17.2571])\n",
      "Epoch: 3476,Loss: 2.927844\n",
      "\tgrad: tensor([-0.0014,  0.0081])\n",
      "\tparams: tensor([  5.3593, -17.2572])\n",
      "Epoch: 3477,Loss: 2.927844\n",
      "\tgrad: tensor([-0.0014,  0.0081])\n",
      "\tparams: tensor([  5.3593, -17.2573])\n",
      "Epoch: 3478,Loss: 2.927844\n",
      "\tgrad: tensor([-0.0014,  0.0081])\n",
      "\tparams: tensor([  5.3593, -17.2574])\n",
      "Epoch: 3479,Loss: 2.927843\n",
      "\tgrad: tensor([-0.0014,  0.0081])\n",
      "\tparams: tensor([  5.3594, -17.2575])\n",
      "Epoch: 3480,Loss: 2.927843\n",
      "\tgrad: tensor([-0.0014,  0.0080])\n",
      "\tparams: tensor([  5.3594, -17.2575])\n",
      "Epoch: 3481,Loss: 2.927842\n",
      "\tgrad: tensor([-0.0014,  0.0080])\n",
      "\tparams: tensor([  5.3594, -17.2576])\n",
      "Epoch: 3482,Loss: 2.927840\n",
      "\tgrad: tensor([-0.0014,  0.0080])\n",
      "\tparams: tensor([  5.3594, -17.2577])\n",
      "Epoch: 3483,Loss: 2.927842\n",
      "\tgrad: tensor([-0.0014,  0.0080])\n",
      "\tparams: tensor([  5.3594, -17.2578])\n",
      "Epoch: 3484,Loss: 2.927839\n",
      "\tgrad: tensor([-0.0014,  0.0080])\n",
      "\tparams: tensor([  5.3594, -17.2579])\n",
      "Epoch: 3485,Loss: 2.927838\n",
      "\tgrad: tensor([-0.0014,  0.0080])\n",
      "\tparams: tensor([  5.3594, -17.2579])\n",
      "Epoch: 3486,Loss: 2.927839\n",
      "\tgrad: tensor([-0.0014,  0.0080])\n",
      "\tparams: tensor([  5.3595, -17.2580])\n",
      "Epoch: 3487,Loss: 2.927838\n",
      "\tgrad: tensor([-0.0014,  0.0079])\n",
      "\tparams: tensor([  5.3595, -17.2581])\n",
      "Epoch: 3488,Loss: 2.927837\n",
      "\tgrad: tensor([-0.0014,  0.0079])\n",
      "\tparams: tensor([  5.3595, -17.2582])\n",
      "Epoch: 3489,Loss: 2.927835\n",
      "\tgrad: tensor([-0.0014,  0.0079])\n",
      "\tparams: tensor([  5.3595, -17.2583])\n",
      "Epoch: 3490,Loss: 2.927837\n",
      "\tgrad: tensor([-0.0014,  0.0079])\n",
      "\tparams: tensor([  5.3595, -17.2583])\n",
      "Epoch: 3491,Loss: 2.927836\n",
      "\tgrad: tensor([-0.0014,  0.0079])\n",
      "\tparams: tensor([  5.3595, -17.2584])\n",
      "Epoch: 3492,Loss: 2.927835\n",
      "\tgrad: tensor([-0.0014,  0.0079])\n",
      "\tparams: tensor([  5.3595, -17.2585])\n",
      "Epoch: 3493,Loss: 2.927833\n",
      "\tgrad: tensor([-0.0014,  0.0079])\n",
      "\tparams: tensor([  5.3596, -17.2586])\n",
      "Epoch: 3494,Loss: 2.927833\n",
      "\tgrad: tensor([-0.0014,  0.0079])\n",
      "\tparams: tensor([  5.3596, -17.2587])\n",
      "Epoch: 3495,Loss: 2.927833\n",
      "\tgrad: tensor([-0.0014,  0.0078])\n",
      "\tparams: tensor([  5.3596, -17.2587])\n",
      "Epoch: 3496,Loss: 2.927832\n",
      "\tgrad: tensor([-0.0014,  0.0078])\n",
      "\tparams: tensor([  5.3596, -17.2588])\n",
      "Epoch: 3497,Loss: 2.927831\n",
      "\tgrad: tensor([-0.0014,  0.0078])\n",
      "\tparams: tensor([  5.3596, -17.2589])\n",
      "Epoch: 3498,Loss: 2.927830\n",
      "\tgrad: tensor([-0.0014,  0.0078])\n",
      "\tparams: tensor([  5.3596, -17.2590])\n",
      "Epoch: 3499,Loss: 2.927830\n",
      "\tgrad: tensor([-0.0014,  0.0078])\n",
      "\tparams: tensor([  5.3596, -17.2590])\n",
      "Epoch: 3500,Loss: 2.927830\n",
      "\tgrad: tensor([-0.0014,  0.0078])\n",
      "\tparams: tensor([  5.3597, -17.2591])\n",
      "Epoch: 3501,Loss: 2.927829\n",
      "\tgrad: tensor([-0.0014,  0.0078])\n",
      "\tparams: tensor([  5.3597, -17.2592])\n",
      "Epoch: 3502,Loss: 2.927828\n",
      "\tgrad: tensor([-0.0014,  0.0077])\n",
      "\tparams: tensor([  5.3597, -17.2593])\n",
      "Epoch: 3503,Loss: 2.927828\n",
      "\tgrad: tensor([-0.0014,  0.0077])\n",
      "\tparams: tensor([  5.3597, -17.2594])\n",
      "Epoch: 3504,Loss: 2.927827\n",
      "\tgrad: tensor([-0.0014,  0.0077])\n",
      "\tparams: tensor([  5.3597, -17.2594])\n",
      "Epoch: 3505,Loss: 2.927825\n",
      "\tgrad: tensor([-0.0014,  0.0077])\n",
      "\tparams: tensor([  5.3597, -17.2595])\n",
      "Epoch: 3506,Loss: 2.927827\n",
      "\tgrad: tensor([-0.0014,  0.0077])\n",
      "\tparams: tensor([  5.3597, -17.2596])\n",
      "Epoch: 3507,Loss: 2.927825\n",
      "\tgrad: tensor([-0.0014,  0.0077])\n",
      "\tparams: tensor([  5.3597, -17.2597])\n",
      "Epoch: 3508,Loss: 2.927824\n",
      "\tgrad: tensor([-0.0013,  0.0077])\n",
      "\tparams: tensor([  5.3598, -17.2597])\n",
      "Epoch: 3509,Loss: 2.927824\n",
      "\tgrad: tensor([-0.0013,  0.0077])\n",
      "\tparams: tensor([  5.3598, -17.2598])\n",
      "Epoch: 3510,Loss: 2.927824\n",
      "\tgrad: tensor([-0.0013,  0.0076])\n",
      "\tparams: tensor([  5.3598, -17.2599])\n",
      "Epoch: 3511,Loss: 2.927822\n",
      "\tgrad: tensor([-0.0014,  0.0076])\n",
      "\tparams: tensor([  5.3598, -17.2600])\n",
      "Epoch: 3512,Loss: 2.927822\n",
      "\tgrad: tensor([-0.0014,  0.0076])\n",
      "\tparams: tensor([  5.3598, -17.2600])\n",
      "Epoch: 3513,Loss: 2.927821\n",
      "\tgrad: tensor([-0.0013,  0.0076])\n",
      "\tparams: tensor([  5.3598, -17.2601])\n",
      "Epoch: 3514,Loss: 2.927820\n",
      "\tgrad: tensor([-0.0013,  0.0076])\n",
      "\tparams: tensor([  5.3598, -17.2602])\n",
      "Epoch: 3515,Loss: 2.927820\n",
      "\tgrad: tensor([-0.0014,  0.0076])\n",
      "\tparams: tensor([  5.3599, -17.2603])\n",
      "Epoch: 3516,Loss: 2.927821\n",
      "\tgrad: tensor([-0.0014,  0.0076])\n",
      "\tparams: tensor([  5.3599, -17.2604])\n",
      "Epoch: 3517,Loss: 2.927819\n",
      "\tgrad: tensor([-0.0014,  0.0075])\n",
      "\tparams: tensor([  5.3599, -17.2604])\n",
      "Epoch: 3518,Loss: 2.927819\n",
      "\tgrad: tensor([-0.0014,  0.0075])\n",
      "\tparams: tensor([  5.3599, -17.2605])\n",
      "Epoch: 3519,Loss: 2.927819\n",
      "\tgrad: tensor([-0.0013,  0.0075])\n",
      "\tparams: tensor([  5.3599, -17.2606])\n",
      "Epoch: 3520,Loss: 2.927817\n",
      "\tgrad: tensor([-0.0013,  0.0075])\n",
      "\tparams: tensor([  5.3599, -17.2607])\n",
      "Epoch: 3521,Loss: 2.927817\n",
      "\tgrad: tensor([-0.0013,  0.0075])\n",
      "\tparams: tensor([  5.3599, -17.2607])\n",
      "Epoch: 3522,Loss: 2.927816\n",
      "\tgrad: tensor([-0.0013,  0.0075])\n",
      "\tparams: tensor([  5.3599, -17.2608])\n",
      "Epoch: 3523,Loss: 2.927815\n",
      "\tgrad: tensor([-0.0013,  0.0075])\n",
      "\tparams: tensor([  5.3600, -17.2609])\n",
      "Epoch: 3524,Loss: 2.927816\n",
      "\tgrad: tensor([-0.0013,  0.0075])\n",
      "\tparams: tensor([  5.3600, -17.2610])\n",
      "Epoch: 3525,Loss: 2.927815\n",
      "\tgrad: tensor([-0.0013,  0.0074])\n",
      "\tparams: tensor([  5.3600, -17.2610])\n",
      "Epoch: 3526,Loss: 2.927814\n",
      "\tgrad: tensor([-0.0013,  0.0074])\n",
      "\tparams: tensor([  5.3600, -17.2611])\n",
      "Epoch: 3527,Loss: 2.927813\n",
      "\tgrad: tensor([-0.0013,  0.0074])\n",
      "\tparams: tensor([  5.3600, -17.2612])\n",
      "Epoch: 3528,Loss: 2.927812\n",
      "\tgrad: tensor([-0.0013,  0.0074])\n",
      "\tparams: tensor([  5.3600, -17.2612])\n",
      "Epoch: 3529,Loss: 2.927811\n",
      "\tgrad: tensor([-0.0013,  0.0074])\n",
      "\tparams: tensor([  5.3600, -17.2613])\n",
      "Epoch: 3530,Loss: 2.927812\n",
      "\tgrad: tensor([-0.0013,  0.0074])\n",
      "\tparams: tensor([  5.3601, -17.2614])\n",
      "Epoch: 3531,Loss: 2.927812\n",
      "\tgrad: tensor([-0.0013,  0.0074])\n",
      "\tparams: tensor([  5.3601, -17.2615])\n",
      "Epoch: 3532,Loss: 2.927810\n",
      "\tgrad: tensor([-0.0013,  0.0074])\n",
      "\tparams: tensor([  5.3601, -17.2615])\n",
      "Epoch: 3533,Loss: 2.927809\n",
      "\tgrad: tensor([-0.0013,  0.0073])\n",
      "\tparams: tensor([  5.3601, -17.2616])\n",
      "Epoch: 3534,Loss: 2.927810\n",
      "\tgrad: tensor([-0.0013,  0.0073])\n",
      "\tparams: tensor([  5.3601, -17.2617])\n",
      "Epoch: 3535,Loss: 2.927809\n",
      "\tgrad: tensor([-0.0013,  0.0073])\n",
      "\tparams: tensor([  5.3601, -17.2618])\n",
      "Epoch: 3536,Loss: 2.927808\n",
      "\tgrad: tensor([-0.0013,  0.0073])\n",
      "\tparams: tensor([  5.3601, -17.2618])\n",
      "Epoch: 3537,Loss: 2.927808\n",
      "\tgrad: tensor([-0.0013,  0.0073])\n",
      "\tparams: tensor([  5.3601, -17.2619])\n",
      "Epoch: 3538,Loss: 2.927806\n",
      "\tgrad: tensor([-0.0013,  0.0073])\n",
      "\tparams: tensor([  5.3602, -17.2620])\n",
      "Epoch: 3539,Loss: 2.927806\n",
      "\tgrad: tensor([-0.0013,  0.0073])\n",
      "\tparams: tensor([  5.3602, -17.2621])\n",
      "Epoch: 3540,Loss: 2.927805\n",
      "\tgrad: tensor([-0.0013,  0.0073])\n",
      "\tparams: tensor([  5.3602, -17.2621])\n",
      "Epoch: 3541,Loss: 2.927804\n",
      "\tgrad: tensor([-0.0013,  0.0073])\n",
      "\tparams: tensor([  5.3602, -17.2622])\n",
      "Epoch: 3542,Loss: 2.927805\n",
      "\tgrad: tensor([-0.0013,  0.0072])\n",
      "\tparams: tensor([  5.3602, -17.2623])\n",
      "Epoch: 3543,Loss: 2.927804\n",
      "\tgrad: tensor([-0.0013,  0.0072])\n",
      "\tparams: tensor([  5.3602, -17.2623])\n",
      "Epoch: 3544,Loss: 2.927805\n",
      "\tgrad: tensor([-0.0013,  0.0072])\n",
      "\tparams: tensor([  5.3602, -17.2624])\n",
      "Epoch: 3545,Loss: 2.927804\n",
      "\tgrad: tensor([-0.0013,  0.0072])\n",
      "\tparams: tensor([  5.3602, -17.2625])\n",
      "Epoch: 3546,Loss: 2.927804\n",
      "\tgrad: tensor([-0.0013,  0.0072])\n",
      "\tparams: tensor([  5.3603, -17.2626])\n",
      "Epoch: 3547,Loss: 2.927803\n",
      "\tgrad: tensor([-0.0013,  0.0072])\n",
      "\tparams: tensor([  5.3603, -17.2626])\n",
      "Epoch: 3548,Loss: 2.927802\n",
      "\tgrad: tensor([-0.0013,  0.0072])\n",
      "\tparams: tensor([  5.3603, -17.2627])\n",
      "Epoch: 3549,Loss: 2.927801\n",
      "\tgrad: tensor([-0.0013,  0.0071])\n",
      "\tparams: tensor([  5.3603, -17.2628])\n",
      "Epoch: 3550,Loss: 2.927801\n",
      "\tgrad: tensor([-0.0013,  0.0071])\n",
      "\tparams: tensor([  5.3603, -17.2628])\n",
      "Epoch: 3551,Loss: 2.927799\n",
      "\tgrad: tensor([-0.0012,  0.0071])\n",
      "\tparams: tensor([  5.3603, -17.2629])\n",
      "Epoch: 3552,Loss: 2.927801\n",
      "\tgrad: tensor([-0.0012,  0.0071])\n",
      "\tparams: tensor([  5.3603, -17.2630])\n",
      "Epoch: 3553,Loss: 2.927798\n",
      "\tgrad: tensor([-0.0012,  0.0071])\n",
      "\tparams: tensor([  5.3603, -17.2631])\n",
      "Epoch: 3554,Loss: 2.927798\n",
      "\tgrad: tensor([-0.0012,  0.0071])\n",
      "\tparams: tensor([  5.3604, -17.2631])\n",
      "Epoch: 3555,Loss: 2.927798\n",
      "\tgrad: tensor([-0.0013,  0.0071])\n",
      "\tparams: tensor([  5.3604, -17.2632])\n",
      "Epoch: 3556,Loss: 2.927798\n",
      "\tgrad: tensor([-0.0013,  0.0071])\n",
      "\tparams: tensor([  5.3604, -17.2633])\n",
      "Epoch: 3557,Loss: 2.927798\n",
      "\tgrad: tensor([-0.0013,  0.0071])\n",
      "\tparams: tensor([  5.3604, -17.2633])\n",
      "Epoch: 3558,Loss: 2.927796\n",
      "\tgrad: tensor([-0.0013,  0.0070])\n",
      "\tparams: tensor([  5.3604, -17.2634])\n",
      "Epoch: 3559,Loss: 2.927795\n",
      "\tgrad: tensor([-0.0013,  0.0070])\n",
      "\tparams: tensor([  5.3604, -17.2635])\n",
      "Epoch: 3560,Loss: 2.927796\n",
      "\tgrad: tensor([-0.0013,  0.0070])\n",
      "\tparams: tensor([  5.3604, -17.2636])\n",
      "Epoch: 3561,Loss: 2.927794\n",
      "\tgrad: tensor([-0.0013,  0.0070])\n",
      "\tparams: tensor([  5.3604, -17.2636])\n",
      "Epoch: 3562,Loss: 2.927795\n",
      "\tgrad: tensor([-0.0013,  0.0070])\n",
      "\tparams: tensor([  5.3605, -17.2637])\n",
      "Epoch: 3563,Loss: 2.927795\n",
      "\tgrad: tensor([-0.0013,  0.0070])\n",
      "\tparams: tensor([  5.3605, -17.2638])\n",
      "Epoch: 3564,Loss: 2.927793\n",
      "\tgrad: tensor([-0.0013,  0.0070])\n",
      "\tparams: tensor([  5.3605, -17.2638])\n",
      "Epoch: 3565,Loss: 2.927795\n",
      "\tgrad: tensor([-0.0012,  0.0070])\n",
      "\tparams: tensor([  5.3605, -17.2639])\n",
      "Epoch: 3566,Loss: 2.927791\n",
      "\tgrad: tensor([-0.0012,  0.0069])\n",
      "\tparams: tensor([  5.3605, -17.2640])\n",
      "Epoch: 3567,Loss: 2.927791\n",
      "\tgrad: tensor([-0.0012,  0.0069])\n",
      "\tparams: tensor([  5.3605, -17.2640])\n",
      "Epoch: 3568,Loss: 2.927791\n",
      "\tgrad: tensor([-0.0012,  0.0069])\n",
      "\tparams: tensor([  5.3605, -17.2641])\n",
      "Epoch: 3569,Loss: 2.927790\n",
      "\tgrad: tensor([-0.0012,  0.0069])\n",
      "\tparams: tensor([  5.3605, -17.2642])\n",
      "Epoch: 3570,Loss: 2.927790\n",
      "\tgrad: tensor([-0.0012,  0.0069])\n",
      "\tparams: tensor([  5.3606, -17.2642])\n",
      "Epoch: 3571,Loss: 2.927789\n",
      "\tgrad: tensor([-0.0012,  0.0069])\n",
      "\tparams: tensor([  5.3606, -17.2643])\n",
      "Epoch: 3572,Loss: 2.927790\n",
      "\tgrad: tensor([-0.0012,  0.0069])\n",
      "\tparams: tensor([  5.3606, -17.2644])\n",
      "Epoch: 3573,Loss: 2.927789\n",
      "\tgrad: tensor([-0.0012,  0.0069])\n",
      "\tparams: tensor([  5.3606, -17.2645])\n",
      "Epoch: 3574,Loss: 2.927789\n",
      "\tgrad: tensor([-0.0012,  0.0069])\n",
      "\tparams: tensor([  5.3606, -17.2645])\n",
      "Epoch: 3575,Loss: 2.927789\n",
      "\tgrad: tensor([-0.0012,  0.0068])\n",
      "\tparams: tensor([  5.3606, -17.2646])\n",
      "Epoch: 3576,Loss: 2.927787\n",
      "\tgrad: tensor([-0.0012,  0.0068])\n",
      "\tparams: tensor([  5.3606, -17.2647])\n",
      "Epoch: 3577,Loss: 2.927786\n",
      "\tgrad: tensor([-0.0012,  0.0068])\n",
      "\tparams: tensor([  5.3606, -17.2647])\n",
      "Epoch: 3578,Loss: 2.927788\n",
      "\tgrad: tensor([-0.0012,  0.0068])\n",
      "\tparams: tensor([  5.3607, -17.2648])\n",
      "Epoch: 3579,Loss: 2.927785\n",
      "\tgrad: tensor([-0.0012,  0.0068])\n",
      "\tparams: tensor([  5.3607, -17.2649])\n",
      "Epoch: 3580,Loss: 2.927785\n",
      "\tgrad: tensor([-0.0012,  0.0068])\n",
      "\tparams: tensor([  5.3607, -17.2649])\n",
      "Epoch: 3581,Loss: 2.927786\n",
      "\tgrad: tensor([-0.0012,  0.0068])\n",
      "\tparams: tensor([  5.3607, -17.2650])\n",
      "Epoch: 3582,Loss: 2.927785\n",
      "\tgrad: tensor([-0.0012,  0.0068])\n",
      "\tparams: tensor([  5.3607, -17.2651])\n",
      "Epoch: 3583,Loss: 2.927784\n",
      "\tgrad: tensor([-0.0012,  0.0067])\n",
      "\tparams: tensor([  5.3607, -17.2651])\n",
      "Epoch: 3584,Loss: 2.927784\n",
      "\tgrad: tensor([-0.0012,  0.0067])\n",
      "\tparams: tensor([  5.3607, -17.2652])\n",
      "Epoch: 3585,Loss: 2.927783\n",
      "\tgrad: tensor([-0.0012,  0.0067])\n",
      "\tparams: tensor([  5.3607, -17.2653])\n",
      "Epoch: 3586,Loss: 2.927783\n",
      "\tgrad: tensor([-0.0012,  0.0067])\n",
      "\tparams: tensor([  5.3607, -17.2653])\n",
      "Epoch: 3587,Loss: 2.927781\n",
      "\tgrad: tensor([-0.0012,  0.0067])\n",
      "\tparams: tensor([  5.3608, -17.2654])\n",
      "Epoch: 3588,Loss: 2.927782\n",
      "\tgrad: tensor([-0.0012,  0.0067])\n",
      "\tparams: tensor([  5.3608, -17.2655])\n",
      "Epoch: 3589,Loss: 2.927781\n",
      "\tgrad: tensor([-0.0012,  0.0067])\n",
      "\tparams: tensor([  5.3608, -17.2655])\n",
      "Epoch: 3590,Loss: 2.927781\n",
      "\tgrad: tensor([-0.0012,  0.0067])\n",
      "\tparams: tensor([  5.3608, -17.2656])\n",
      "Epoch: 3591,Loss: 2.927781\n",
      "\tgrad: tensor([-0.0012,  0.0067])\n",
      "\tparams: tensor([  5.3608, -17.2657])\n",
      "Epoch: 3592,Loss: 2.927780\n",
      "\tgrad: tensor([-0.0012,  0.0066])\n",
      "\tparams: tensor([  5.3608, -17.2657])\n",
      "Epoch: 3593,Loss: 2.927780\n",
      "\tgrad: tensor([-0.0012,  0.0066])\n",
      "\tparams: tensor([  5.3608, -17.2658])\n",
      "Epoch: 3594,Loss: 2.927778\n",
      "\tgrad: tensor([-0.0012,  0.0066])\n",
      "\tparams: tensor([  5.3608, -17.2659])\n",
      "Epoch: 3595,Loss: 2.927779\n",
      "\tgrad: tensor([-0.0012,  0.0066])\n",
      "\tparams: tensor([  5.3609, -17.2659])\n",
      "Epoch: 3596,Loss: 2.927778\n",
      "\tgrad: tensor([-0.0012,  0.0066])\n",
      "\tparams: tensor([  5.3609, -17.2660])\n",
      "Epoch: 3597,Loss: 2.927778\n",
      "\tgrad: tensor([-0.0012,  0.0066])\n",
      "\tparams: tensor([  5.3609, -17.2661])\n",
      "Epoch: 3598,Loss: 2.927779\n",
      "\tgrad: tensor([-0.0012,  0.0066])\n",
      "\tparams: tensor([  5.3609, -17.2661])\n",
      "Epoch: 3599,Loss: 2.927777\n",
      "\tgrad: tensor([-0.0012,  0.0066])\n",
      "\tparams: tensor([  5.3609, -17.2662])\n",
      "Epoch: 3600,Loss: 2.927776\n",
      "\tgrad: tensor([-0.0012,  0.0066])\n",
      "\tparams: tensor([  5.3609, -17.2663])\n",
      "Epoch: 3601,Loss: 2.927775\n",
      "\tgrad: tensor([-0.0012,  0.0065])\n",
      "\tparams: tensor([  5.3609, -17.2663])\n",
      "Epoch: 3602,Loss: 2.927776\n",
      "\tgrad: tensor([-0.0012,  0.0065])\n",
      "\tparams: tensor([  5.3609, -17.2664])\n",
      "Epoch: 3603,Loss: 2.927773\n",
      "\tgrad: tensor([-0.0012,  0.0065])\n",
      "\tparams: tensor([  5.3609, -17.2665])\n",
      "Epoch: 3604,Loss: 2.927775\n",
      "\tgrad: tensor([-0.0012,  0.0065])\n",
      "\tparams: tensor([  5.3610, -17.2665])\n",
      "Epoch: 3605,Loss: 2.927775\n",
      "\tgrad: tensor([-0.0011,  0.0065])\n",
      "\tparams: tensor([  5.3610, -17.2666])\n",
      "Epoch: 3606,Loss: 2.927775\n",
      "\tgrad: tensor([-0.0011,  0.0065])\n",
      "\tparams: tensor([  5.3610, -17.2667])\n",
      "Epoch: 3607,Loss: 2.927773\n",
      "\tgrad: tensor([-0.0011,  0.0065])\n",
      "\tparams: tensor([  5.3610, -17.2667])\n",
      "Epoch: 3608,Loss: 2.927773\n",
      "\tgrad: tensor([-0.0011,  0.0065])\n",
      "\tparams: tensor([  5.3610, -17.2668])\n",
      "Epoch: 3609,Loss: 2.927773\n",
      "\tgrad: tensor([-0.0011,  0.0065])\n",
      "\tparams: tensor([  5.3610, -17.2668])\n",
      "Epoch: 3610,Loss: 2.927772\n",
      "\tgrad: tensor([-0.0011,  0.0064])\n",
      "\tparams: tensor([  5.3610, -17.2669])\n",
      "Epoch: 3611,Loss: 2.927772\n",
      "\tgrad: tensor([-0.0011,  0.0064])\n",
      "\tparams: tensor([  5.3610, -17.2670])\n",
      "Epoch: 3612,Loss: 2.927770\n",
      "\tgrad: tensor([-0.0011,  0.0064])\n",
      "\tparams: tensor([  5.3611, -17.2670])\n",
      "Epoch: 3613,Loss: 2.927772\n",
      "\tgrad: tensor([-0.0011,  0.0064])\n",
      "\tparams: tensor([  5.3611, -17.2671])\n",
      "Epoch: 3614,Loss: 2.927771\n",
      "\tgrad: tensor([-0.0011,  0.0064])\n",
      "\tparams: tensor([  5.3611, -17.2672])\n",
      "Epoch: 3615,Loss: 2.927770\n",
      "\tgrad: tensor([-0.0011,  0.0064])\n",
      "\tparams: tensor([  5.3611, -17.2672])\n",
      "Epoch: 3616,Loss: 2.927770\n",
      "\tgrad: tensor([-0.0011,  0.0064])\n",
      "\tparams: tensor([  5.3611, -17.2673])\n",
      "Epoch: 3617,Loss: 2.927769\n",
      "\tgrad: tensor([-0.0011,  0.0064])\n",
      "\tparams: tensor([  5.3611, -17.2674])\n",
      "Epoch: 3618,Loss: 2.927768\n",
      "\tgrad: tensor([-0.0011,  0.0064])\n",
      "\tparams: tensor([  5.3611, -17.2674])\n",
      "Epoch: 3619,Loss: 2.927769\n",
      "\tgrad: tensor([-0.0011,  0.0064])\n",
      "\tparams: tensor([  5.3611, -17.2675])\n",
      "Epoch: 3620,Loss: 2.927768\n",
      "\tgrad: tensor([-0.0011,  0.0063])\n",
      "\tparams: tensor([  5.3611, -17.2675])\n",
      "Epoch: 3621,Loss: 2.927767\n",
      "\tgrad: tensor([-0.0011,  0.0063])\n",
      "\tparams: tensor([  5.3612, -17.2676])\n",
      "Epoch: 3622,Loss: 2.927767\n",
      "\tgrad: tensor([-0.0011,  0.0063])\n",
      "\tparams: tensor([  5.3612, -17.2677])\n",
      "Epoch: 3623,Loss: 2.927767\n",
      "\tgrad: tensor([-0.0011,  0.0063])\n",
      "\tparams: tensor([  5.3612, -17.2677])\n",
      "Epoch: 3624,Loss: 2.927765\n",
      "\tgrad: tensor([-0.0011,  0.0063])\n",
      "\tparams: tensor([  5.3612, -17.2678])\n",
      "Epoch: 3625,Loss: 2.927766\n",
      "\tgrad: tensor([-0.0011,  0.0063])\n",
      "\tparams: tensor([  5.3612, -17.2679])\n",
      "Epoch: 3626,Loss: 2.927765\n",
      "\tgrad: tensor([-0.0011,  0.0063])\n",
      "\tparams: tensor([  5.3612, -17.2679])\n",
      "Epoch: 3627,Loss: 2.927765\n",
      "\tgrad: tensor([-0.0011,  0.0063])\n",
      "\tparams: tensor([  5.3612, -17.2680])\n",
      "Epoch: 3628,Loss: 2.927764\n",
      "\tgrad: tensor([-0.0011,  0.0063])\n",
      "\tparams: tensor([  5.3612, -17.2681])\n",
      "Epoch: 3629,Loss: 2.927764\n",
      "\tgrad: tensor([-0.0011,  0.0062])\n",
      "\tparams: tensor([  5.3612, -17.2681])\n",
      "Epoch: 3630,Loss: 2.927764\n",
      "\tgrad: tensor([-0.0011,  0.0062])\n",
      "\tparams: tensor([  5.3613, -17.2682])\n",
      "Epoch: 3631,Loss: 2.927762\n",
      "\tgrad: tensor([-0.0011,  0.0062])\n",
      "\tparams: tensor([  5.3613, -17.2682])\n",
      "Epoch: 3632,Loss: 2.927763\n",
      "\tgrad: tensor([-0.0011,  0.0062])\n",
      "\tparams: tensor([  5.3613, -17.2683])\n",
      "Epoch: 3633,Loss: 2.927763\n",
      "\tgrad: tensor([-0.0011,  0.0062])\n",
      "\tparams: tensor([  5.3613, -17.2684])\n",
      "Epoch: 3634,Loss: 2.927762\n",
      "\tgrad: tensor([-0.0011,  0.0062])\n",
      "\tparams: tensor([  5.3613, -17.2684])\n",
      "Epoch: 3635,Loss: 2.927761\n",
      "\tgrad: tensor([-0.0011,  0.0062])\n",
      "\tparams: tensor([  5.3613, -17.2685])\n",
      "Epoch: 3636,Loss: 2.927762\n",
      "\tgrad: tensor([-0.0011,  0.0062])\n",
      "\tparams: tensor([  5.3613, -17.2685])\n",
      "Epoch: 3637,Loss: 2.927759\n",
      "\tgrad: tensor([-0.0011,  0.0062])\n",
      "\tparams: tensor([  5.3613, -17.2686])\n",
      "Epoch: 3638,Loss: 2.927761\n",
      "\tgrad: tensor([-0.0011,  0.0061])\n",
      "\tparams: tensor([  5.3613, -17.2687])\n",
      "Epoch: 3639,Loss: 2.927761\n",
      "\tgrad: tensor([-0.0011,  0.0061])\n",
      "\tparams: tensor([  5.3614, -17.2687])\n",
      "Epoch: 3640,Loss: 2.927760\n",
      "\tgrad: tensor([-0.0011,  0.0061])\n",
      "\tparams: tensor([  5.3614, -17.2688])\n",
      "Epoch: 3641,Loss: 2.927759\n",
      "\tgrad: tensor([-0.0011,  0.0061])\n",
      "\tparams: tensor([  5.3614, -17.2689])\n",
      "Epoch: 3642,Loss: 2.927758\n",
      "\tgrad: tensor([-0.0011,  0.0061])\n",
      "\tparams: tensor([  5.3614, -17.2689])\n",
      "Epoch: 3643,Loss: 2.927759\n",
      "\tgrad: tensor([-0.0011,  0.0061])\n",
      "\tparams: tensor([  5.3614, -17.2690])\n",
      "Epoch: 3644,Loss: 2.927757\n",
      "\tgrad: tensor([-0.0011,  0.0061])\n",
      "\tparams: tensor([  5.3614, -17.2690])\n",
      "Epoch: 3645,Loss: 2.927758\n",
      "\tgrad: tensor([-0.0011,  0.0061])\n",
      "\tparams: tensor([  5.3614, -17.2691])\n",
      "Epoch: 3646,Loss: 2.927757\n",
      "\tgrad: tensor([-0.0011,  0.0061])\n",
      "\tparams: tensor([  5.3614, -17.2692])\n",
      "Epoch: 3647,Loss: 2.927757\n",
      "\tgrad: tensor([-0.0011,  0.0061])\n",
      "\tparams: tensor([  5.3614, -17.2692])\n",
      "Epoch: 3648,Loss: 2.927757\n",
      "\tgrad: tensor([-0.0011,  0.0060])\n",
      "\tparams: tensor([  5.3614, -17.2693])\n",
      "Epoch: 3649,Loss: 2.927756\n",
      "\tgrad: tensor([-0.0011,  0.0060])\n",
      "\tparams: tensor([  5.3615, -17.2693])\n",
      "Epoch: 3650,Loss: 2.927757\n",
      "\tgrad: tensor([-0.0011,  0.0060])\n",
      "\tparams: tensor([  5.3615, -17.2694])\n",
      "Epoch: 3651,Loss: 2.927756\n",
      "\tgrad: tensor([-0.0011,  0.0060])\n",
      "\tparams: tensor([  5.3615, -17.2695])\n",
      "Epoch: 3652,Loss: 2.927756\n",
      "\tgrad: tensor([-0.0010,  0.0060])\n",
      "\tparams: tensor([  5.3615, -17.2695])\n",
      "Epoch: 3653,Loss: 2.927755\n",
      "\tgrad: tensor([-0.0010,  0.0060])\n",
      "\tparams: tensor([  5.3615, -17.2696])\n",
      "Epoch: 3654,Loss: 2.927755\n",
      "\tgrad: tensor([-0.0010,  0.0060])\n",
      "\tparams: tensor([  5.3615, -17.2696])\n",
      "Epoch: 3655,Loss: 2.927754\n",
      "\tgrad: tensor([-0.0010,  0.0060])\n",
      "\tparams: tensor([  5.3615, -17.2697])\n",
      "Epoch: 3656,Loss: 2.927754\n",
      "\tgrad: tensor([-0.0010,  0.0060])\n",
      "\tparams: tensor([  5.3615, -17.2698])\n",
      "Epoch: 3657,Loss: 2.927755\n",
      "\tgrad: tensor([-0.0010,  0.0060])\n",
      "\tparams: tensor([  5.3615, -17.2698])\n",
      "Epoch: 3658,Loss: 2.927753\n",
      "\tgrad: tensor([-0.0010,  0.0059])\n",
      "\tparams: tensor([  5.3616, -17.2699])\n",
      "Epoch: 3659,Loss: 2.927752\n",
      "\tgrad: tensor([-0.0010,  0.0059])\n",
      "\tparams: tensor([  5.3616, -17.2699])\n",
      "Epoch: 3660,Loss: 2.927754\n",
      "\tgrad: tensor([-0.0010,  0.0059])\n",
      "\tparams: tensor([  5.3616, -17.2700])\n",
      "Epoch: 3661,Loss: 2.927752\n",
      "\tgrad: tensor([-0.0010,  0.0059])\n",
      "\tparams: tensor([  5.3616, -17.2701])\n",
      "Epoch: 3662,Loss: 2.927751\n",
      "\tgrad: tensor([-0.0010,  0.0059])\n",
      "\tparams: tensor([  5.3616, -17.2701])\n",
      "Epoch: 3663,Loss: 2.927752\n",
      "\tgrad: tensor([-0.0010,  0.0059])\n",
      "\tparams: tensor([  5.3616, -17.2702])\n",
      "Epoch: 3664,Loss: 2.927750\n",
      "\tgrad: tensor([-0.0011,  0.0059])\n",
      "\tparams: tensor([  5.3616, -17.2702])\n",
      "Epoch: 3665,Loss: 2.927749\n",
      "\tgrad: tensor([-0.0010,  0.0059])\n",
      "\tparams: tensor([  5.3616, -17.2703])\n",
      "Epoch: 3666,Loss: 2.927751\n",
      "\tgrad: tensor([-0.0010,  0.0059])\n",
      "\tparams: tensor([  5.3616, -17.2703])\n",
      "Epoch: 3667,Loss: 2.927750\n",
      "\tgrad: tensor([-0.0010,  0.0058])\n",
      "\tparams: tensor([  5.3616, -17.2704])\n",
      "Epoch: 3668,Loss: 2.927750\n",
      "\tgrad: tensor([-0.0010,  0.0058])\n",
      "\tparams: tensor([  5.3617, -17.2705])\n",
      "Epoch: 3669,Loss: 2.927747\n",
      "\tgrad: tensor([-0.0010,  0.0058])\n",
      "\tparams: tensor([  5.3617, -17.2705])\n",
      "Epoch: 3670,Loss: 2.927749\n",
      "\tgrad: tensor([-0.0010,  0.0058])\n",
      "\tparams: tensor([  5.3617, -17.2706])\n",
      "Epoch: 3671,Loss: 2.927747\n",
      "\tgrad: tensor([-0.0010,  0.0058])\n",
      "\tparams: tensor([  5.3617, -17.2706])\n",
      "Epoch: 3672,Loss: 2.927748\n",
      "\tgrad: tensor([-0.0010,  0.0058])\n",
      "\tparams: tensor([  5.3617, -17.2707])\n",
      "Epoch: 3673,Loss: 2.927748\n",
      "\tgrad: tensor([-0.0010,  0.0058])\n",
      "\tparams: tensor([  5.3617, -17.2708])\n",
      "Epoch: 3674,Loss: 2.927747\n",
      "\tgrad: tensor([-0.0010,  0.0058])\n",
      "\tparams: tensor([  5.3617, -17.2708])\n",
      "Epoch: 3675,Loss: 2.927747\n",
      "\tgrad: tensor([-0.0010,  0.0058])\n",
      "\tparams: tensor([  5.3617, -17.2709])\n",
      "Epoch: 3676,Loss: 2.927748\n",
      "\tgrad: tensor([-0.0010,  0.0058])\n",
      "\tparams: tensor([  5.3617, -17.2709])\n",
      "Epoch: 3677,Loss: 2.927747\n",
      "\tgrad: tensor([-0.0010,  0.0058])\n",
      "\tparams: tensor([  5.3617, -17.2710])\n",
      "Epoch: 3678,Loss: 2.927747\n",
      "\tgrad: tensor([-0.0010,  0.0057])\n",
      "\tparams: tensor([  5.3618, -17.2710])\n",
      "Epoch: 3679,Loss: 2.927745\n",
      "\tgrad: tensor([-0.0010,  0.0057])\n",
      "\tparams: tensor([  5.3618, -17.2711])\n",
      "Epoch: 3680,Loss: 2.927745\n",
      "\tgrad: tensor([-0.0010,  0.0057])\n",
      "\tparams: tensor([  5.3618, -17.2712])\n",
      "Epoch: 3681,Loss: 2.927746\n",
      "\tgrad: tensor([-0.0010,  0.0057])\n",
      "\tparams: tensor([  5.3618, -17.2712])\n",
      "Epoch: 3682,Loss: 2.927744\n",
      "\tgrad: tensor([-0.0010,  0.0057])\n",
      "\tparams: tensor([  5.3618, -17.2713])\n",
      "Epoch: 3683,Loss: 2.927743\n",
      "\tgrad: tensor([-0.0010,  0.0057])\n",
      "\tparams: tensor([  5.3618, -17.2713])\n",
      "Epoch: 3684,Loss: 2.927743\n",
      "\tgrad: tensor([-0.0010,  0.0057])\n",
      "\tparams: tensor([  5.3618, -17.2714])\n",
      "Epoch: 3685,Loss: 2.927743\n",
      "\tgrad: tensor([-0.0010,  0.0057])\n",
      "\tparams: tensor([  5.3618, -17.2714])\n",
      "Epoch: 3686,Loss: 2.927743\n",
      "\tgrad: tensor([-0.0010,  0.0057])\n",
      "\tparams: tensor([  5.3618, -17.2715])\n",
      "Epoch: 3687,Loss: 2.927743\n",
      "\tgrad: tensor([-0.0010,  0.0056])\n",
      "\tparams: tensor([  5.3618, -17.2716])\n",
      "Epoch: 3688,Loss: 2.927744\n",
      "\tgrad: tensor([-0.0010,  0.0056])\n",
      "\tparams: tensor([  5.3619, -17.2716])\n",
      "Epoch: 3689,Loss: 2.927742\n",
      "\tgrad: tensor([-0.0010,  0.0056])\n",
      "\tparams: tensor([  5.3619, -17.2717])\n",
      "Epoch: 3690,Loss: 2.927742\n",
      "\tgrad: tensor([-0.0010,  0.0056])\n",
      "\tparams: tensor([  5.3619, -17.2717])\n",
      "Epoch: 3691,Loss: 2.927742\n",
      "\tgrad: tensor([-0.0010,  0.0056])\n",
      "\tparams: tensor([  5.3619, -17.2718])\n",
      "Epoch: 3692,Loss: 2.927742\n",
      "\tgrad: tensor([-0.0010,  0.0056])\n",
      "\tparams: tensor([  5.3619, -17.2718])\n",
      "Epoch: 3693,Loss: 2.927741\n",
      "\tgrad: tensor([-0.0010,  0.0056])\n",
      "\tparams: tensor([  5.3619, -17.2719])\n",
      "Epoch: 3694,Loss: 2.927741\n",
      "\tgrad: tensor([-0.0010,  0.0056])\n",
      "\tparams: tensor([  5.3619, -17.2719])\n",
      "Epoch: 3695,Loss: 2.927741\n",
      "\tgrad: tensor([-0.0010,  0.0056])\n",
      "\tparams: tensor([  5.3619, -17.2720])\n",
      "Epoch: 3696,Loss: 2.927742\n",
      "\tgrad: tensor([-0.0010,  0.0056])\n",
      "\tparams: tensor([  5.3619, -17.2721])\n",
      "Epoch: 3697,Loss: 2.927741\n",
      "\tgrad: tensor([-0.0010,  0.0056])\n",
      "\tparams: tensor([  5.3619, -17.2721])\n",
      "Epoch: 3698,Loss: 2.927741\n",
      "\tgrad: tensor([-0.0010,  0.0056])\n",
      "\tparams: tensor([  5.3620, -17.2722])\n",
      "Epoch: 3699,Loss: 2.927740\n",
      "\tgrad: tensor([-0.0010,  0.0055])\n",
      "\tparams: tensor([  5.3620, -17.2722])\n",
      "Epoch: 3700,Loss: 2.927739\n",
      "\tgrad: tensor([-0.0010,  0.0055])\n",
      "\tparams: tensor([  5.3620, -17.2723])\n",
      "Epoch: 3701,Loss: 2.927738\n",
      "\tgrad: tensor([-0.0010,  0.0055])\n",
      "\tparams: tensor([  5.3620, -17.2723])\n",
      "Epoch: 3702,Loss: 2.927738\n",
      "\tgrad: tensor([-0.0010,  0.0055])\n",
      "\tparams: tensor([  5.3620, -17.2724])\n",
      "Epoch: 3703,Loss: 2.927737\n",
      "\tgrad: tensor([-0.0010,  0.0055])\n",
      "\tparams: tensor([  5.3620, -17.2724])\n",
      "Epoch: 3704,Loss: 2.927737\n",
      "\tgrad: tensor([-0.0010,  0.0055])\n",
      "\tparams: tensor([  5.3620, -17.2725])\n",
      "Epoch: 3705,Loss: 2.927738\n",
      "\tgrad: tensor([-0.0010,  0.0055])\n",
      "\tparams: tensor([  5.3620, -17.2726])\n",
      "Epoch: 3706,Loss: 2.927737\n",
      "\tgrad: tensor([-0.0010,  0.0055])\n",
      "\tparams: tensor([  5.3620, -17.2726])\n",
      "Epoch: 3707,Loss: 2.927736\n",
      "\tgrad: tensor([-0.0010,  0.0055])\n",
      "\tparams: tensor([  5.3620, -17.2727])\n",
      "Epoch: 3708,Loss: 2.927737\n",
      "\tgrad: tensor([-0.0010,  0.0055])\n",
      "\tparams: tensor([  5.3621, -17.2727])\n",
      "Epoch: 3709,Loss: 2.927737\n",
      "\tgrad: tensor([-0.0010,  0.0054])\n",
      "\tparams: tensor([  5.3621, -17.2728])\n",
      "Epoch: 3710,Loss: 2.927736\n",
      "\tgrad: tensor([-0.0010,  0.0054])\n",
      "\tparams: tensor([  5.3621, -17.2728])\n",
      "Epoch: 3711,Loss: 2.927734\n",
      "\tgrad: tensor([-0.0010,  0.0054])\n",
      "\tparams: tensor([  5.3621, -17.2729])\n",
      "Epoch: 3712,Loss: 2.927735\n",
      "\tgrad: tensor([-0.0010,  0.0054])\n",
      "\tparams: tensor([  5.3621, -17.2729])\n",
      "Epoch: 3713,Loss: 2.927735\n",
      "\tgrad: tensor([-0.0009,  0.0054])\n",
      "\tparams: tensor([  5.3621, -17.2730])\n",
      "Epoch: 3714,Loss: 2.927734\n",
      "\tgrad: tensor([-0.0009,  0.0054])\n",
      "\tparams: tensor([  5.3621, -17.2730])\n",
      "Epoch: 3715,Loss: 2.927734\n",
      "\tgrad: tensor([-0.0009,  0.0054])\n",
      "\tparams: tensor([  5.3621, -17.2731])\n",
      "Epoch: 3716,Loss: 2.927733\n",
      "\tgrad: tensor([-0.0009,  0.0054])\n",
      "\tparams: tensor([  5.3621, -17.2732])\n",
      "Epoch: 3717,Loss: 2.927734\n",
      "\tgrad: tensor([-0.0009,  0.0054])\n",
      "\tparams: tensor([  5.3621, -17.2732])\n",
      "Epoch: 3718,Loss: 2.927733\n",
      "\tgrad: tensor([-0.0009,  0.0054])\n",
      "\tparams: tensor([  5.3622, -17.2733])\n",
      "Epoch: 3719,Loss: 2.927733\n",
      "\tgrad: tensor([-0.0009,  0.0054])\n",
      "\tparams: tensor([  5.3622, -17.2733])\n",
      "Epoch: 3720,Loss: 2.927733\n",
      "\tgrad: tensor([-0.0010,  0.0053])\n",
      "\tparams: tensor([  5.3622, -17.2734])\n",
      "Epoch: 3721,Loss: 2.927732\n",
      "\tgrad: tensor([-0.0009,  0.0053])\n",
      "\tparams: tensor([  5.3622, -17.2734])\n",
      "Epoch: 3722,Loss: 2.927731\n",
      "\tgrad: tensor([-0.0009,  0.0053])\n",
      "\tparams: tensor([  5.3622, -17.2735])\n",
      "Epoch: 3723,Loss: 2.927731\n",
      "\tgrad: tensor([-0.0009,  0.0053])\n",
      "\tparams: tensor([  5.3622, -17.2735])\n",
      "Epoch: 3724,Loss: 2.927733\n",
      "\tgrad: tensor([-0.0009,  0.0053])\n",
      "\tparams: tensor([  5.3622, -17.2736])\n",
      "Epoch: 3725,Loss: 2.927730\n",
      "\tgrad: tensor([-0.0009,  0.0053])\n",
      "\tparams: tensor([  5.3622, -17.2736])\n",
      "Epoch: 3726,Loss: 2.927730\n",
      "\tgrad: tensor([-0.0009,  0.0053])\n",
      "\tparams: tensor([  5.3622, -17.2737])\n",
      "Epoch: 3727,Loss: 2.927732\n",
      "\tgrad: tensor([-0.0009,  0.0053])\n",
      "\tparams: tensor([  5.3622, -17.2737])\n",
      "Epoch: 3728,Loss: 2.927730\n",
      "\tgrad: tensor([-0.0010,  0.0053])\n",
      "\tparams: tensor([  5.3622, -17.2738])\n",
      "Epoch: 3729,Loss: 2.927732\n",
      "\tgrad: tensor([-0.0009,  0.0053])\n",
      "\tparams: tensor([  5.3623, -17.2738])\n",
      "Epoch: 3730,Loss: 2.927731\n",
      "\tgrad: tensor([-0.0009,  0.0053])\n",
      "\tparams: tensor([  5.3623, -17.2739])\n",
      "Epoch: 3731,Loss: 2.927730\n",
      "\tgrad: tensor([-0.0009,  0.0052])\n",
      "\tparams: tensor([  5.3623, -17.2740])\n",
      "Epoch: 3732,Loss: 2.927728\n",
      "\tgrad: tensor([-0.0009,  0.0052])\n",
      "\tparams: tensor([  5.3623, -17.2740])\n",
      "Epoch: 3733,Loss: 2.927729\n",
      "\tgrad: tensor([-0.0009,  0.0052])\n",
      "\tparams: tensor([  5.3623, -17.2741])\n",
      "Epoch: 3734,Loss: 2.927729\n",
      "\tgrad: tensor([-0.0009,  0.0052])\n",
      "\tparams: tensor([  5.3623, -17.2741])\n",
      "Epoch: 3735,Loss: 2.927728\n",
      "\tgrad: tensor([-0.0009,  0.0052])\n",
      "\tparams: tensor([  5.3623, -17.2742])\n",
      "Epoch: 3736,Loss: 2.927728\n",
      "\tgrad: tensor([-0.0009,  0.0052])\n",
      "\tparams: tensor([  5.3623, -17.2742])\n",
      "Epoch: 3737,Loss: 2.927728\n",
      "\tgrad: tensor([-0.0009,  0.0052])\n",
      "\tparams: tensor([  5.3623, -17.2743])\n",
      "Epoch: 3738,Loss: 2.927728\n",
      "\tgrad: tensor([-0.0009,  0.0052])\n",
      "\tparams: tensor([  5.3623, -17.2743])\n",
      "Epoch: 3739,Loss: 2.927727\n",
      "\tgrad: tensor([-0.0009,  0.0052])\n",
      "\tparams: tensor([  5.3623, -17.2744])\n",
      "Epoch: 3740,Loss: 2.927728\n",
      "\tgrad: tensor([-0.0009,  0.0052])\n",
      "\tparams: tensor([  5.3624, -17.2744])\n",
      "Epoch: 3741,Loss: 2.927728\n",
      "\tgrad: tensor([-0.0009,  0.0052])\n",
      "\tparams: tensor([  5.3624, -17.2745])\n",
      "Epoch: 3742,Loss: 2.927727\n",
      "\tgrad: tensor([-0.0009,  0.0051])\n",
      "\tparams: tensor([  5.3624, -17.2745])\n",
      "Epoch: 3743,Loss: 2.927727\n",
      "\tgrad: tensor([-0.0009,  0.0051])\n",
      "\tparams: tensor([  5.3624, -17.2746])\n",
      "Epoch: 3744,Loss: 2.927726\n",
      "\tgrad: tensor([-0.0009,  0.0051])\n",
      "\tparams: tensor([  5.3624, -17.2746])\n",
      "Epoch: 3745,Loss: 2.927726\n",
      "\tgrad: tensor([-0.0009,  0.0051])\n",
      "\tparams: tensor([  5.3624, -17.2747])\n",
      "Epoch: 3746,Loss: 2.927725\n",
      "\tgrad: tensor([-0.0009,  0.0051])\n",
      "\tparams: tensor([  5.3624, -17.2747])\n",
      "Epoch: 3747,Loss: 2.927725\n",
      "\tgrad: tensor([-0.0009,  0.0051])\n",
      "\tparams: tensor([  5.3624, -17.2748])\n",
      "Epoch: 3748,Loss: 2.927725\n",
      "\tgrad: tensor([-0.0009,  0.0051])\n",
      "\tparams: tensor([  5.3624, -17.2748])\n",
      "Epoch: 3749,Loss: 2.927723\n",
      "\tgrad: tensor([-0.0009,  0.0051])\n",
      "\tparams: tensor([  5.3624, -17.2749])\n",
      "Epoch: 3750,Loss: 2.927724\n",
      "\tgrad: tensor([-0.0009,  0.0051])\n",
      "\tparams: tensor([  5.3624, -17.2749])\n",
      "Epoch: 3751,Loss: 2.927724\n",
      "\tgrad: tensor([-0.0009,  0.0051])\n",
      "\tparams: tensor([  5.3625, -17.2750])\n",
      "Epoch: 3752,Loss: 2.927725\n",
      "\tgrad: tensor([-0.0009,  0.0051])\n",
      "\tparams: tensor([  5.3625, -17.2750])\n",
      "Epoch: 3753,Loss: 2.927724\n",
      "\tgrad: tensor([-0.0009,  0.0051])\n",
      "\tparams: tensor([  5.3625, -17.2751])\n",
      "Epoch: 3754,Loss: 2.927724\n",
      "\tgrad: tensor([-0.0009,  0.0050])\n",
      "\tparams: tensor([  5.3625, -17.2751])\n",
      "Epoch: 3755,Loss: 2.927723\n",
      "\tgrad: tensor([-0.0009,  0.0050])\n",
      "\tparams: tensor([  5.3625, -17.2752])\n",
      "Epoch: 3756,Loss: 2.927723\n",
      "\tgrad: tensor([-0.0009,  0.0050])\n",
      "\tparams: tensor([  5.3625, -17.2752])\n",
      "Epoch: 3757,Loss: 2.927723\n",
      "\tgrad: tensor([-0.0009,  0.0050])\n",
      "\tparams: tensor([  5.3625, -17.2753])\n",
      "Epoch: 3758,Loss: 2.927722\n",
      "\tgrad: tensor([-0.0009,  0.0050])\n",
      "\tparams: tensor([  5.3625, -17.2753])\n",
      "Epoch: 3759,Loss: 2.927723\n",
      "\tgrad: tensor([-0.0009,  0.0050])\n",
      "\tparams: tensor([  5.3625, -17.2754])\n",
      "Epoch: 3760,Loss: 2.927722\n",
      "\tgrad: tensor([-0.0009,  0.0050])\n",
      "\tparams: tensor([  5.3625, -17.2754])\n",
      "Epoch: 3761,Loss: 2.927723\n",
      "\tgrad: tensor([-0.0009,  0.0050])\n",
      "\tparams: tensor([  5.3625, -17.2755])\n",
      "Epoch: 3762,Loss: 2.927721\n",
      "\tgrad: tensor([-0.0009,  0.0050])\n",
      "\tparams: tensor([  5.3626, -17.2755])\n",
      "Epoch: 3763,Loss: 2.927722\n",
      "\tgrad: tensor([-0.0009,  0.0050])\n",
      "\tparams: tensor([  5.3626, -17.2756])\n",
      "Epoch: 3764,Loss: 2.927720\n",
      "\tgrad: tensor([-0.0009,  0.0050])\n",
      "\tparams: tensor([  5.3626, -17.2756])\n",
      "Epoch: 3765,Loss: 2.927720\n",
      "\tgrad: tensor([-0.0009,  0.0050])\n",
      "\tparams: tensor([  5.3626, -17.2757])\n",
      "Epoch: 3766,Loss: 2.927719\n",
      "\tgrad: tensor([-0.0009,  0.0049])\n",
      "\tparams: tensor([  5.3626, -17.2757])\n",
      "Epoch: 3767,Loss: 2.927721\n",
      "\tgrad: tensor([-0.0009,  0.0049])\n",
      "\tparams: tensor([  5.3626, -17.2758])\n",
      "Epoch: 3768,Loss: 2.927719\n",
      "\tgrad: tensor([-0.0009,  0.0049])\n",
      "\tparams: tensor([  5.3626, -17.2758])\n",
      "Epoch: 3769,Loss: 2.927719\n",
      "\tgrad: tensor([-0.0009,  0.0049])\n",
      "\tparams: tensor([  5.3626, -17.2759])\n",
      "Epoch: 3770,Loss: 2.927719\n",
      "\tgrad: tensor([-0.0009,  0.0049])\n",
      "\tparams: tensor([  5.3626, -17.2759])\n",
      "Epoch: 3771,Loss: 2.927719\n",
      "\tgrad: tensor([-0.0009,  0.0049])\n",
      "\tparams: tensor([  5.3626, -17.2760])\n",
      "Epoch: 3772,Loss: 2.927719\n",
      "\tgrad: tensor([-0.0009,  0.0049])\n",
      "\tparams: tensor([  5.3626, -17.2760])\n",
      "Epoch: 3773,Loss: 2.927720\n",
      "\tgrad: tensor([-0.0009,  0.0049])\n",
      "\tparams: tensor([  5.3626, -17.2761])\n",
      "Epoch: 3774,Loss: 2.927718\n",
      "\tgrad: tensor([-0.0009,  0.0049])\n",
      "\tparams: tensor([  5.3627, -17.2761])\n",
      "Epoch: 3775,Loss: 2.927718\n",
      "\tgrad: tensor([-0.0009,  0.0049])\n",
      "\tparams: tensor([  5.3627, -17.2762])\n",
      "Epoch: 3776,Loss: 2.927717\n",
      "\tgrad: tensor([-0.0009,  0.0049])\n",
      "\tparams: tensor([  5.3627, -17.2762])\n",
      "Epoch: 3777,Loss: 2.927718\n",
      "\tgrad: tensor([-0.0008,  0.0049])\n",
      "\tparams: tensor([  5.3627, -17.2763])\n",
      "Epoch: 3778,Loss: 2.927717\n",
      "\tgrad: tensor([-0.0008,  0.0048])\n",
      "\tparams: tensor([  5.3627, -17.2763])\n",
      "Epoch: 3779,Loss: 2.927717\n",
      "\tgrad: tensor([-0.0008,  0.0048])\n",
      "\tparams: tensor([  5.3627, -17.2764])\n",
      "Epoch: 3780,Loss: 2.927716\n",
      "\tgrad: tensor([-0.0008,  0.0048])\n",
      "\tparams: tensor([  5.3627, -17.2764])\n",
      "Epoch: 3781,Loss: 2.927716\n",
      "\tgrad: tensor([-0.0008,  0.0048])\n",
      "\tparams: tensor([  5.3627, -17.2765])\n",
      "Epoch: 3782,Loss: 2.927717\n",
      "\tgrad: tensor([-0.0008,  0.0048])\n",
      "\tparams: tensor([  5.3627, -17.2765])\n",
      "Epoch: 3783,Loss: 2.927717\n",
      "\tgrad: tensor([-0.0008,  0.0048])\n",
      "\tparams: tensor([  5.3627, -17.2766])\n",
      "Epoch: 3784,Loss: 2.927716\n",
      "\tgrad: tensor([-0.0009,  0.0048])\n",
      "\tparams: tensor([  5.3627, -17.2766])\n",
      "Epoch: 3785,Loss: 2.927715\n",
      "\tgrad: tensor([-0.0008,  0.0048])\n",
      "\tparams: tensor([  5.3627, -17.2767])\n",
      "Epoch: 3786,Loss: 2.927715\n",
      "\tgrad: tensor([-0.0008,  0.0048])\n",
      "\tparams: tensor([  5.3628, -17.2767])\n",
      "Epoch: 3787,Loss: 2.927715\n",
      "\tgrad: tensor([-0.0008,  0.0048])\n",
      "\tparams: tensor([  5.3628, -17.2767])\n",
      "Epoch: 3788,Loss: 2.927715\n",
      "\tgrad: tensor([-0.0008,  0.0048])\n",
      "\tparams: tensor([  5.3628, -17.2768])\n",
      "Epoch: 3789,Loss: 2.927715\n",
      "\tgrad: tensor([-0.0008,  0.0048])\n",
      "\tparams: tensor([  5.3628, -17.2768])\n",
      "Epoch: 3790,Loss: 2.927715\n",
      "\tgrad: tensor([-0.0008,  0.0047])\n",
      "\tparams: tensor([  5.3628, -17.2769])\n",
      "Epoch: 3791,Loss: 2.927714\n",
      "\tgrad: tensor([-0.0008,  0.0047])\n",
      "\tparams: tensor([  5.3628, -17.2769])\n",
      "Epoch: 3792,Loss: 2.927714\n",
      "\tgrad: tensor([-0.0008,  0.0047])\n",
      "\tparams: tensor([  5.3628, -17.2770])\n",
      "Epoch: 3793,Loss: 2.927714\n",
      "\tgrad: tensor([-0.0008,  0.0047])\n",
      "\tparams: tensor([  5.3628, -17.2770])\n",
      "Epoch: 3794,Loss: 2.927714\n",
      "\tgrad: tensor([-0.0008,  0.0047])\n",
      "\tparams: tensor([  5.3628, -17.2771])\n",
      "Epoch: 3795,Loss: 2.927713\n",
      "\tgrad: tensor([-0.0008,  0.0047])\n",
      "\tparams: tensor([  5.3628, -17.2771])\n",
      "Epoch: 3796,Loss: 2.927714\n",
      "\tgrad: tensor([-0.0008,  0.0047])\n",
      "\tparams: tensor([  5.3628, -17.2772])\n",
      "Epoch: 3797,Loss: 2.927713\n",
      "\tgrad: tensor([-0.0008,  0.0047])\n",
      "\tparams: tensor([  5.3629, -17.2772])\n",
      "Epoch: 3798,Loss: 2.927712\n",
      "\tgrad: tensor([-0.0008,  0.0047])\n",
      "\tparams: tensor([  5.3629, -17.2773])\n",
      "Epoch: 3799,Loss: 2.927712\n",
      "\tgrad: tensor([-0.0008,  0.0047])\n",
      "\tparams: tensor([  5.3629, -17.2773])\n",
      "Epoch: 3800,Loss: 2.927713\n",
      "\tgrad: tensor([-0.0008,  0.0047])\n",
      "\tparams: tensor([  5.3629, -17.2774])\n",
      "Epoch: 3801,Loss: 2.927711\n",
      "\tgrad: tensor([-0.0008,  0.0047])\n",
      "\tparams: tensor([  5.3629, -17.2774])\n",
      "Epoch: 3802,Loss: 2.927712\n",
      "\tgrad: tensor([-0.0008,  0.0047])\n",
      "\tparams: tensor([  5.3629, -17.2775])\n",
      "Epoch: 3803,Loss: 2.927712\n",
      "\tgrad: tensor([-0.0008,  0.0046])\n",
      "\tparams: tensor([  5.3629, -17.2775])\n",
      "Epoch: 3804,Loss: 2.927711\n",
      "\tgrad: tensor([-0.0008,  0.0046])\n",
      "\tparams: tensor([  5.3629, -17.2775])\n",
      "Epoch: 3805,Loss: 2.927712\n",
      "\tgrad: tensor([-0.0008,  0.0046])\n",
      "\tparams: tensor([  5.3629, -17.2776])\n",
      "Epoch: 3806,Loss: 2.927711\n",
      "\tgrad: tensor([-0.0008,  0.0046])\n",
      "\tparams: tensor([  5.3629, -17.2776])\n",
      "Epoch: 3807,Loss: 2.927711\n",
      "\tgrad: tensor([-0.0008,  0.0046])\n",
      "\tparams: tensor([  5.3629, -17.2777])\n",
      "Epoch: 3808,Loss: 2.927711\n",
      "\tgrad: tensor([-0.0008,  0.0046])\n",
      "\tparams: tensor([  5.3629, -17.2777])\n",
      "Epoch: 3809,Loss: 2.927709\n",
      "\tgrad: tensor([-0.0008,  0.0046])\n",
      "\tparams: tensor([  5.3629, -17.2778])\n",
      "Epoch: 3810,Loss: 2.927710\n",
      "\tgrad: tensor([-0.0008,  0.0046])\n",
      "\tparams: tensor([  5.3630, -17.2778])\n",
      "Epoch: 3811,Loss: 2.927710\n",
      "\tgrad: tensor([-0.0008,  0.0046])\n",
      "\tparams: tensor([  5.3630, -17.2779])\n",
      "Epoch: 3812,Loss: 2.927708\n",
      "\tgrad: tensor([-0.0008,  0.0046])\n",
      "\tparams: tensor([  5.3630, -17.2779])\n",
      "Epoch: 3813,Loss: 2.927708\n",
      "\tgrad: tensor([-0.0008,  0.0046])\n",
      "\tparams: tensor([  5.3630, -17.2780])\n",
      "Epoch: 3814,Loss: 2.927709\n",
      "\tgrad: tensor([-0.0008,  0.0046])\n",
      "\tparams: tensor([  5.3630, -17.2780])\n",
      "Epoch: 3815,Loss: 2.927709\n",
      "\tgrad: tensor([-0.0008,  0.0045])\n",
      "\tparams: tensor([  5.3630, -17.2781])\n",
      "Epoch: 3816,Loss: 2.927710\n",
      "\tgrad: tensor([-0.0008,  0.0045])\n",
      "\tparams: tensor([  5.3630, -17.2781])\n",
      "Epoch: 3817,Loss: 2.927708\n",
      "\tgrad: tensor([-0.0008,  0.0045])\n",
      "\tparams: tensor([  5.3630, -17.2781])\n",
      "Epoch: 3818,Loss: 2.927708\n",
      "\tgrad: tensor([-0.0008,  0.0045])\n",
      "\tparams: tensor([  5.3630, -17.2782])\n",
      "Epoch: 3819,Loss: 2.927706\n",
      "\tgrad: tensor([-0.0008,  0.0045])\n",
      "\tparams: tensor([  5.3630, -17.2782])\n",
      "Epoch: 3820,Loss: 2.927707\n",
      "\tgrad: tensor([-0.0008,  0.0045])\n",
      "\tparams: tensor([  5.3630, -17.2783])\n",
      "Epoch: 3821,Loss: 2.927708\n",
      "\tgrad: tensor([-0.0008,  0.0045])\n",
      "\tparams: tensor([  5.3630, -17.2783])\n",
      "Epoch: 3822,Loss: 2.927707\n",
      "\tgrad: tensor([-0.0008,  0.0045])\n",
      "\tparams: tensor([  5.3631, -17.2784])\n",
      "Epoch: 3823,Loss: 2.927707\n",
      "\tgrad: tensor([-0.0008,  0.0045])\n",
      "\tparams: tensor([  5.3631, -17.2784])\n",
      "Epoch: 3824,Loss: 2.927707\n",
      "\tgrad: tensor([-0.0008,  0.0045])\n",
      "\tparams: tensor([  5.3631, -17.2785])\n",
      "Epoch: 3825,Loss: 2.927708\n",
      "\tgrad: tensor([-0.0008,  0.0045])\n",
      "\tparams: tensor([  5.3631, -17.2785])\n",
      "Epoch: 3826,Loss: 2.927707\n",
      "\tgrad: tensor([-0.0008,  0.0045])\n",
      "\tparams: tensor([  5.3631, -17.2786])\n",
      "Epoch: 3827,Loss: 2.927706\n",
      "\tgrad: tensor([-0.0008,  0.0045])\n",
      "\tparams: tensor([  5.3631, -17.2786])\n",
      "Epoch: 3828,Loss: 2.927707\n",
      "\tgrad: tensor([-0.0008,  0.0044])\n",
      "\tparams: tensor([  5.3631, -17.2786])\n",
      "Epoch: 3829,Loss: 2.927705\n",
      "\tgrad: tensor([-0.0008,  0.0044])\n",
      "\tparams: tensor([  5.3631, -17.2787])\n",
      "Epoch: 3830,Loss: 2.927706\n",
      "\tgrad: tensor([-0.0008,  0.0044])\n",
      "\tparams: tensor([  5.3631, -17.2787])\n",
      "Epoch: 3831,Loss: 2.927706\n",
      "\tgrad: tensor([-0.0008,  0.0044])\n",
      "\tparams: tensor([  5.3631, -17.2788])\n",
      "Epoch: 3832,Loss: 2.927705\n",
      "\tgrad: tensor([-0.0008,  0.0044])\n",
      "\tparams: tensor([  5.3631, -17.2788])\n",
      "Epoch: 3833,Loss: 2.927705\n",
      "\tgrad: tensor([-0.0008,  0.0044])\n",
      "\tparams: tensor([  5.3631, -17.2789])\n",
      "Epoch: 3834,Loss: 2.927705\n",
      "\tgrad: tensor([-0.0008,  0.0044])\n",
      "\tparams: tensor([  5.3631, -17.2789])\n",
      "Epoch: 3835,Loss: 2.927705\n",
      "\tgrad: tensor([-0.0008,  0.0044])\n",
      "\tparams: tensor([  5.3632, -17.2789])\n",
      "Epoch: 3836,Loss: 2.927705\n",
      "\tgrad: tensor([-0.0008,  0.0044])\n",
      "\tparams: tensor([  5.3632, -17.2790])\n",
      "Epoch: 3837,Loss: 2.927705\n",
      "\tgrad: tensor([-0.0008,  0.0044])\n",
      "\tparams: tensor([  5.3632, -17.2790])\n",
      "Epoch: 3838,Loss: 2.927704\n",
      "\tgrad: tensor([-0.0008,  0.0044])\n",
      "\tparams: tensor([  5.3632, -17.2791])\n",
      "Epoch: 3839,Loss: 2.927704\n",
      "\tgrad: tensor([-0.0008,  0.0044])\n",
      "\tparams: tensor([  5.3632, -17.2791])\n",
      "Epoch: 3840,Loss: 2.927704\n",
      "\tgrad: tensor([-0.0008,  0.0044])\n",
      "\tparams: tensor([  5.3632, -17.2792])\n",
      "Epoch: 3841,Loss: 2.927703\n",
      "\tgrad: tensor([-0.0008,  0.0044])\n",
      "\tparams: tensor([  5.3632, -17.2792])\n",
      "Epoch: 3842,Loss: 2.927702\n",
      "\tgrad: tensor([-0.0008,  0.0043])\n",
      "\tparams: tensor([  5.3632, -17.2793])\n",
      "Epoch: 3843,Loss: 2.927703\n",
      "\tgrad: tensor([-0.0008,  0.0043])\n",
      "\tparams: tensor([  5.3632, -17.2793])\n",
      "Epoch: 3844,Loss: 2.927703\n",
      "\tgrad: tensor([-0.0008,  0.0043])\n",
      "\tparams: tensor([  5.3632, -17.2793])\n",
      "Epoch: 3845,Loss: 2.927704\n",
      "\tgrad: tensor([-0.0008,  0.0043])\n",
      "\tparams: tensor([  5.3632, -17.2794])\n",
      "Epoch: 3846,Loss: 2.927702\n",
      "\tgrad: tensor([-0.0008,  0.0043])\n",
      "\tparams: tensor([  5.3632, -17.2794])\n",
      "Epoch: 3847,Loss: 2.927701\n",
      "\tgrad: tensor([-0.0008,  0.0043])\n",
      "\tparams: tensor([  5.3632, -17.2795])\n",
      "Epoch: 3848,Loss: 2.927703\n",
      "\tgrad: tensor([-0.0008,  0.0043])\n",
      "\tparams: tensor([  5.3633, -17.2795])\n",
      "Epoch: 3849,Loss: 2.927702\n",
      "\tgrad: tensor([-0.0008,  0.0043])\n",
      "\tparams: tensor([  5.3633, -17.2796])\n",
      "Epoch: 3850,Loss: 2.927701\n",
      "\tgrad: tensor([-0.0007,  0.0043])\n",
      "\tparams: tensor([  5.3633, -17.2796])\n",
      "Epoch: 3851,Loss: 2.927701\n",
      "\tgrad: tensor([-0.0007,  0.0043])\n",
      "\tparams: tensor([  5.3633, -17.2796])\n",
      "Epoch: 3852,Loss: 2.927703\n",
      "\tgrad: tensor([-0.0007,  0.0043])\n",
      "\tparams: tensor([  5.3633, -17.2797])\n",
      "Epoch: 3853,Loss: 2.927700\n",
      "\tgrad: tensor([-0.0007,  0.0043])\n",
      "\tparams: tensor([  5.3633, -17.2797])\n",
      "Epoch: 3854,Loss: 2.927701\n",
      "\tgrad: tensor([-0.0007,  0.0043])\n",
      "\tparams: tensor([  5.3633, -17.2798])\n",
      "Epoch: 3855,Loss: 2.927701\n",
      "\tgrad: tensor([-0.0007,  0.0043])\n",
      "\tparams: tensor([  5.3633, -17.2798])\n",
      "Epoch: 3856,Loss: 2.927700\n",
      "\tgrad: tensor([-0.0007,  0.0042])\n",
      "\tparams: tensor([  5.3633, -17.2799])\n",
      "Epoch: 3857,Loss: 2.927700\n",
      "\tgrad: tensor([-0.0007,  0.0042])\n",
      "\tparams: tensor([  5.3633, -17.2799])\n",
      "Epoch: 3858,Loss: 2.927700\n",
      "\tgrad: tensor([-0.0007,  0.0042])\n",
      "\tparams: tensor([  5.3633, -17.2799])\n",
      "Epoch: 3859,Loss: 2.927701\n",
      "\tgrad: tensor([-0.0007,  0.0042])\n",
      "\tparams: tensor([  5.3633, -17.2800])\n",
      "Epoch: 3860,Loss: 2.927699\n",
      "\tgrad: tensor([-0.0008,  0.0042])\n",
      "\tparams: tensor([  5.3633, -17.2800])\n",
      "Epoch: 3861,Loss: 2.927699\n",
      "\tgrad: tensor([-0.0007,  0.0042])\n",
      "\tparams: tensor([  5.3634, -17.2801])\n",
      "Epoch: 3862,Loss: 2.927700\n",
      "\tgrad: tensor([-0.0007,  0.0042])\n",
      "\tparams: tensor([  5.3634, -17.2801])\n",
      "Epoch: 3863,Loss: 2.927699\n",
      "\tgrad: tensor([-0.0007,  0.0042])\n",
      "\tparams: tensor([  5.3634, -17.2801])\n",
      "Epoch: 3864,Loss: 2.927698\n",
      "\tgrad: tensor([-0.0007,  0.0042])\n",
      "\tparams: tensor([  5.3634, -17.2802])\n",
      "Epoch: 3865,Loss: 2.927699\n",
      "\tgrad: tensor([-0.0007,  0.0042])\n",
      "\tparams: tensor([  5.3634, -17.2802])\n",
      "Epoch: 3866,Loss: 2.927697\n",
      "\tgrad: tensor([-0.0007,  0.0042])\n",
      "\tparams: tensor([  5.3634, -17.2803])\n",
      "Epoch: 3867,Loss: 2.927700\n",
      "\tgrad: tensor([-0.0007,  0.0042])\n",
      "\tparams: tensor([  5.3634, -17.2803])\n",
      "Epoch: 3868,Loss: 2.927699\n",
      "\tgrad: tensor([-0.0007,  0.0042])\n",
      "\tparams: tensor([  5.3634, -17.2804])\n",
      "Epoch: 3869,Loss: 2.927698\n",
      "\tgrad: tensor([-0.0007,  0.0042])\n",
      "\tparams: tensor([  5.3634, -17.2804])\n",
      "Epoch: 3870,Loss: 2.927697\n",
      "\tgrad: tensor([-0.0007,  0.0041])\n",
      "\tparams: tensor([  5.3634, -17.2804])\n",
      "Epoch: 3871,Loss: 2.927698\n",
      "\tgrad: tensor([-0.0007,  0.0041])\n",
      "\tparams: tensor([  5.3634, -17.2805])\n",
      "Epoch: 3872,Loss: 2.927696\n",
      "\tgrad: tensor([-0.0007,  0.0041])\n",
      "\tparams: tensor([  5.3634, -17.2805])\n",
      "Epoch: 3873,Loss: 2.927699\n",
      "\tgrad: tensor([-0.0007,  0.0041])\n",
      "\tparams: tensor([  5.3634, -17.2806])\n",
      "Epoch: 3874,Loss: 2.927698\n",
      "\tgrad: tensor([-0.0007,  0.0041])\n",
      "\tparams: tensor([  5.3634, -17.2806])\n",
      "Epoch: 3875,Loss: 2.927696\n",
      "\tgrad: tensor([-0.0007,  0.0041])\n",
      "\tparams: tensor([  5.3635, -17.2806])\n",
      "Epoch: 3876,Loss: 2.927698\n",
      "\tgrad: tensor([-0.0007,  0.0041])\n",
      "\tparams: tensor([  5.3635, -17.2807])\n",
      "Epoch: 3877,Loss: 2.927697\n",
      "\tgrad: tensor([-0.0007,  0.0041])\n",
      "\tparams: tensor([  5.3635, -17.2807])\n",
      "Epoch: 3878,Loss: 2.927696\n",
      "\tgrad: tensor([-0.0007,  0.0041])\n",
      "\tparams: tensor([  5.3635, -17.2808])\n",
      "Epoch: 3879,Loss: 2.927697\n",
      "\tgrad: tensor([-0.0007,  0.0041])\n",
      "\tparams: tensor([  5.3635, -17.2808])\n",
      "Epoch: 3880,Loss: 2.927696\n",
      "\tgrad: tensor([-0.0007,  0.0041])\n",
      "\tparams: tensor([  5.3635, -17.2808])\n",
      "Epoch: 3881,Loss: 2.927696\n",
      "\tgrad: tensor([-0.0007,  0.0041])\n",
      "\tparams: tensor([  5.3635, -17.2809])\n",
      "Epoch: 3882,Loss: 2.927696\n",
      "\tgrad: tensor([-0.0007,  0.0041])\n",
      "\tparams: tensor([  5.3635, -17.2809])\n",
      "Epoch: 3883,Loss: 2.927696\n",
      "\tgrad: tensor([-0.0007,  0.0041])\n",
      "\tparams: tensor([  5.3635, -17.2810])\n",
      "Epoch: 3884,Loss: 2.927696\n",
      "\tgrad: tensor([-0.0007,  0.0040])\n",
      "\tparams: tensor([  5.3635, -17.2810])\n",
      "Epoch: 3885,Loss: 2.927695\n",
      "\tgrad: tensor([-0.0007,  0.0040])\n",
      "\tparams: tensor([  5.3635, -17.2810])\n",
      "Epoch: 3886,Loss: 2.927696\n",
      "\tgrad: tensor([-0.0007,  0.0040])\n",
      "\tparams: tensor([  5.3635, -17.2811])\n",
      "Epoch: 3887,Loss: 2.927696\n",
      "\tgrad: tensor([-0.0007,  0.0040])\n",
      "\tparams: tensor([  5.3635, -17.2811])\n",
      "Epoch: 3888,Loss: 2.927695\n",
      "\tgrad: tensor([-0.0007,  0.0040])\n",
      "\tparams: tensor([  5.3635, -17.2812])\n",
      "Epoch: 3889,Loss: 2.927695\n",
      "\tgrad: tensor([-0.0007,  0.0040])\n",
      "\tparams: tensor([  5.3636, -17.2812])\n",
      "Epoch: 3890,Loss: 2.927694\n",
      "\tgrad: tensor([-0.0007,  0.0040])\n",
      "\tparams: tensor([  5.3636, -17.2812])\n",
      "Epoch: 3891,Loss: 2.927693\n",
      "\tgrad: tensor([-0.0007,  0.0040])\n",
      "\tparams: tensor([  5.3636, -17.2813])\n",
      "Epoch: 3892,Loss: 2.927693\n",
      "\tgrad: tensor([-0.0007,  0.0040])\n",
      "\tparams: tensor([  5.3636, -17.2813])\n",
      "Epoch: 3893,Loss: 2.927695\n",
      "\tgrad: tensor([-0.0007,  0.0040])\n",
      "\tparams: tensor([  5.3636, -17.2814])\n",
      "Epoch: 3894,Loss: 2.927695\n",
      "\tgrad: tensor([-0.0007,  0.0040])\n",
      "\tparams: tensor([  5.3636, -17.2814])\n",
      "Epoch: 3895,Loss: 2.927694\n",
      "\tgrad: tensor([-0.0007,  0.0040])\n",
      "\tparams: tensor([  5.3636, -17.2815])\n",
      "Epoch: 3896,Loss: 2.927696\n",
      "\tgrad: tensor([-0.0007,  0.0040])\n",
      "\tparams: tensor([  5.3636, -17.2815])\n",
      "Epoch: 3897,Loss: 2.927693\n",
      "\tgrad: tensor([-0.0007,  0.0040])\n",
      "\tparams: tensor([  5.3636, -17.2815])\n",
      "Epoch: 3898,Loss: 2.927693\n",
      "\tgrad: tensor([-0.0007,  0.0039])\n",
      "\tparams: tensor([  5.3636, -17.2816])\n",
      "Epoch: 3899,Loss: 2.927694\n",
      "\tgrad: tensor([-0.0007,  0.0039])\n",
      "\tparams: tensor([  5.3636, -17.2816])\n",
      "Epoch: 3900,Loss: 2.927693\n",
      "\tgrad: tensor([-0.0007,  0.0039])\n",
      "\tparams: tensor([  5.3636, -17.2817])\n",
      "Epoch: 3901,Loss: 2.927692\n",
      "\tgrad: tensor([-0.0007,  0.0039])\n",
      "\tparams: tensor([  5.3636, -17.2817])\n",
      "Epoch: 3902,Loss: 2.927694\n",
      "\tgrad: tensor([-0.0007,  0.0039])\n",
      "\tparams: tensor([  5.3636, -17.2817])\n",
      "Epoch: 3903,Loss: 2.927692\n",
      "\tgrad: tensor([-0.0007,  0.0039])\n",
      "\tparams: tensor([  5.3637, -17.2818])\n",
      "Epoch: 3904,Loss: 2.927693\n",
      "\tgrad: tensor([-0.0007,  0.0039])\n",
      "\tparams: tensor([  5.3637, -17.2818])\n",
      "Epoch: 3905,Loss: 2.927691\n",
      "\tgrad: tensor([-0.0007,  0.0039])\n",
      "\tparams: tensor([  5.3637, -17.2818])\n",
      "Epoch: 3906,Loss: 2.927692\n",
      "\tgrad: tensor([-0.0007,  0.0039])\n",
      "\tparams: tensor([  5.3637, -17.2819])\n",
      "Epoch: 3907,Loss: 2.927692\n",
      "\tgrad: tensor([-0.0007,  0.0039])\n",
      "\tparams: tensor([  5.3637, -17.2819])\n",
      "Epoch: 3908,Loss: 2.927692\n",
      "\tgrad: tensor([-0.0007,  0.0039])\n",
      "\tparams: tensor([  5.3637, -17.2820])\n",
      "Epoch: 3909,Loss: 2.927691\n",
      "\tgrad: tensor([-0.0007,  0.0039])\n",
      "\tparams: tensor([  5.3637, -17.2820])\n",
      "Epoch: 3910,Loss: 2.927692\n",
      "\tgrad: tensor([-0.0007,  0.0039])\n",
      "\tparams: tensor([  5.3637, -17.2820])\n",
      "Epoch: 3911,Loss: 2.927690\n",
      "\tgrad: tensor([-0.0007,  0.0039])\n",
      "\tparams: tensor([  5.3637, -17.2821])\n",
      "Epoch: 3912,Loss: 2.927691\n",
      "\tgrad: tensor([-0.0007,  0.0039])\n",
      "\tparams: tensor([  5.3637, -17.2821])\n",
      "Epoch: 3913,Loss: 2.927691\n",
      "\tgrad: tensor([-0.0007,  0.0039])\n",
      "\tparams: tensor([  5.3637, -17.2822])\n",
      "Epoch: 3914,Loss: 2.927691\n",
      "\tgrad: tensor([-0.0007,  0.0038])\n",
      "\tparams: tensor([  5.3637, -17.2822])\n",
      "Epoch: 3915,Loss: 2.927690\n",
      "\tgrad: tensor([-0.0007,  0.0038])\n",
      "\tparams: tensor([  5.3637, -17.2822])\n",
      "Epoch: 3916,Loss: 2.927691\n",
      "\tgrad: tensor([-0.0007,  0.0038])\n",
      "\tparams: tensor([  5.3637, -17.2823])\n",
      "Epoch: 3917,Loss: 2.927691\n",
      "\tgrad: tensor([-0.0007,  0.0038])\n",
      "\tparams: tensor([  5.3637, -17.2823])\n",
      "Epoch: 3918,Loss: 2.927689\n",
      "\tgrad: tensor([-0.0007,  0.0038])\n",
      "\tparams: tensor([  5.3638, -17.2823])\n",
      "Epoch: 3919,Loss: 2.927690\n",
      "\tgrad: tensor([-0.0007,  0.0038])\n",
      "\tparams: tensor([  5.3638, -17.2824])\n",
      "Epoch: 3920,Loss: 2.927690\n",
      "\tgrad: tensor([-0.0007,  0.0038])\n",
      "\tparams: tensor([  5.3638, -17.2824])\n",
      "Epoch: 3921,Loss: 2.927690\n",
      "\tgrad: tensor([-0.0007,  0.0038])\n",
      "\tparams: tensor([  5.3638, -17.2825])\n",
      "Epoch: 3922,Loss: 2.927690\n",
      "\tgrad: tensor([-0.0007,  0.0038])\n",
      "\tparams: tensor([  5.3638, -17.2825])\n",
      "Epoch: 3923,Loss: 2.927689\n",
      "\tgrad: tensor([-0.0007,  0.0038])\n",
      "\tparams: tensor([  5.3638, -17.2825])\n",
      "Epoch: 3924,Loss: 2.927689\n",
      "\tgrad: tensor([-0.0007,  0.0038])\n",
      "\tparams: tensor([  5.3638, -17.2826])\n",
      "Epoch: 3925,Loss: 2.927689\n",
      "\tgrad: tensor([-0.0007,  0.0038])\n",
      "\tparams: tensor([  5.3638, -17.2826])\n",
      "Epoch: 3926,Loss: 2.927688\n",
      "\tgrad: tensor([-0.0007,  0.0038])\n",
      "\tparams: tensor([  5.3638, -17.2826])\n",
      "Epoch: 3927,Loss: 2.927689\n",
      "\tgrad: tensor([-0.0007,  0.0038])\n",
      "\tparams: tensor([  5.3638, -17.2827])\n",
      "Epoch: 3928,Loss: 2.927689\n",
      "\tgrad: tensor([-0.0007,  0.0038])\n",
      "\tparams: tensor([  5.3638, -17.2827])\n",
      "Epoch: 3929,Loss: 2.927688\n",
      "\tgrad: tensor([-0.0007,  0.0037])\n",
      "\tparams: tensor([  5.3638, -17.2828])\n",
      "Epoch: 3930,Loss: 2.927688\n",
      "\tgrad: tensor([-0.0007,  0.0037])\n",
      "\tparams: tensor([  5.3638, -17.2828])\n",
      "Epoch: 3931,Loss: 2.927688\n",
      "\tgrad: tensor([-0.0007,  0.0037])\n",
      "\tparams: tensor([  5.3638, -17.2828])\n",
      "Epoch: 3932,Loss: 2.927688\n",
      "\tgrad: tensor([-0.0007,  0.0037])\n",
      "\tparams: tensor([  5.3638, -17.2829])\n",
      "Epoch: 3933,Loss: 2.927687\n",
      "\tgrad: tensor([-0.0007,  0.0037])\n",
      "\tparams: tensor([  5.3639, -17.2829])\n",
      "Epoch: 3934,Loss: 2.927689\n",
      "\tgrad: tensor([-0.0006,  0.0037])\n",
      "\tparams: tensor([  5.3639, -17.2829])\n",
      "Epoch: 3935,Loss: 2.927688\n",
      "\tgrad: tensor([-0.0006,  0.0037])\n",
      "\tparams: tensor([  5.3639, -17.2830])\n",
      "Epoch: 3936,Loss: 2.927687\n",
      "\tgrad: tensor([-0.0006,  0.0037])\n",
      "\tparams: tensor([  5.3639, -17.2830])\n",
      "Epoch: 3937,Loss: 2.927687\n",
      "\tgrad: tensor([-0.0006,  0.0037])\n",
      "\tparams: tensor([  5.3639, -17.2831])\n",
      "Epoch: 3938,Loss: 2.927687\n",
      "\tgrad: tensor([-0.0006,  0.0037])\n",
      "\tparams: tensor([  5.3639, -17.2831])\n",
      "Epoch: 3939,Loss: 2.927686\n",
      "\tgrad: tensor([-0.0006,  0.0037])\n",
      "\tparams: tensor([  5.3639, -17.2831])\n",
      "Epoch: 3940,Loss: 2.927686\n",
      "\tgrad: tensor([-0.0007,  0.0037])\n",
      "\tparams: tensor([  5.3639, -17.2832])\n",
      "Epoch: 3941,Loss: 2.927687\n",
      "\tgrad: tensor([-0.0006,  0.0037])\n",
      "\tparams: tensor([  5.3639, -17.2832])\n",
      "Epoch: 3942,Loss: 2.927686\n",
      "\tgrad: tensor([-0.0006,  0.0037])\n",
      "\tparams: tensor([  5.3639, -17.2832])\n",
      "Epoch: 3943,Loss: 2.927686\n",
      "\tgrad: tensor([-0.0006,  0.0037])\n",
      "\tparams: tensor([  5.3639, -17.2833])\n",
      "Epoch: 3944,Loss: 2.927686\n",
      "\tgrad: tensor([-0.0006,  0.0037])\n",
      "\tparams: tensor([  5.3639, -17.2833])\n",
      "Epoch: 3945,Loss: 2.927686\n",
      "\tgrad: tensor([-0.0007,  0.0036])\n",
      "\tparams: tensor([  5.3639, -17.2833])\n",
      "Epoch: 3946,Loss: 2.927685\n",
      "\tgrad: tensor([-0.0006,  0.0036])\n",
      "\tparams: tensor([  5.3639, -17.2834])\n",
      "Epoch: 3947,Loss: 2.927685\n",
      "\tgrad: tensor([-0.0006,  0.0036])\n",
      "\tparams: tensor([  5.3639, -17.2834])\n",
      "Epoch: 3948,Loss: 2.927686\n",
      "\tgrad: tensor([-0.0006,  0.0036])\n",
      "\tparams: tensor([  5.3640, -17.2835])\n",
      "Epoch: 3949,Loss: 2.927685\n",
      "\tgrad: tensor([-0.0006,  0.0036])\n",
      "\tparams: tensor([  5.3640, -17.2835])\n",
      "Epoch: 3950,Loss: 2.927686\n",
      "\tgrad: tensor([-0.0007,  0.0036])\n",
      "\tparams: tensor([  5.3640, -17.2835])\n",
      "Epoch: 3951,Loss: 2.927686\n",
      "\tgrad: tensor([-0.0006,  0.0036])\n",
      "\tparams: tensor([  5.3640, -17.2836])\n",
      "Epoch: 3952,Loss: 2.927687\n",
      "\tgrad: tensor([-0.0006,  0.0036])\n",
      "\tparams: tensor([  5.3640, -17.2836])\n",
      "Epoch: 3953,Loss: 2.927685\n",
      "\tgrad: tensor([-0.0006,  0.0036])\n",
      "\tparams: tensor([  5.3640, -17.2836])\n",
      "Epoch: 3954,Loss: 2.927686\n",
      "\tgrad: tensor([-0.0006,  0.0036])\n",
      "\tparams: tensor([  5.3640, -17.2837])\n",
      "Epoch: 3955,Loss: 2.927686\n",
      "\tgrad: tensor([-0.0006,  0.0036])\n",
      "\tparams: tensor([  5.3640, -17.2837])\n",
      "Epoch: 3956,Loss: 2.927685\n",
      "\tgrad: tensor([-0.0006,  0.0036])\n",
      "\tparams: tensor([  5.3640, -17.2837])\n",
      "Epoch: 3957,Loss: 2.927683\n",
      "\tgrad: tensor([-0.0006,  0.0036])\n",
      "\tparams: tensor([  5.3640, -17.2838])\n",
      "Epoch: 3958,Loss: 2.927684\n",
      "\tgrad: tensor([-0.0007,  0.0036])\n",
      "\tparams: tensor([  5.3640, -17.2838])\n",
      "Epoch: 3959,Loss: 2.927685\n",
      "\tgrad: tensor([-0.0006,  0.0036])\n",
      "\tparams: tensor([  5.3640, -17.2839])\n",
      "Epoch: 3960,Loss: 2.927684\n",
      "\tgrad: tensor([-0.0007,  0.0036])\n",
      "\tparams: tensor([  5.3640, -17.2839])\n",
      "Epoch: 3961,Loss: 2.927684\n",
      "\tgrad: tensor([-0.0006,  0.0035])\n",
      "\tparams: tensor([  5.3640, -17.2839])\n",
      "Epoch: 3962,Loss: 2.927684\n",
      "\tgrad: tensor([-0.0006,  0.0035])\n",
      "\tparams: tensor([  5.3640, -17.2840])\n",
      "Epoch: 3963,Loss: 2.927685\n",
      "\tgrad: tensor([-0.0007,  0.0035])\n",
      "\tparams: tensor([  5.3640, -17.2840])\n",
      "Epoch: 3964,Loss: 2.927683\n",
      "\tgrad: tensor([-0.0006,  0.0035])\n",
      "\tparams: tensor([  5.3641, -17.2840])\n",
      "Epoch: 3965,Loss: 2.927685\n",
      "\tgrad: tensor([-0.0006,  0.0035])\n",
      "\tparams: tensor([  5.3641, -17.2841])\n",
      "Epoch: 3966,Loss: 2.927685\n",
      "\tgrad: tensor([-0.0006,  0.0035])\n",
      "\tparams: tensor([  5.3641, -17.2841])\n",
      "Epoch: 3967,Loss: 2.927684\n",
      "\tgrad: tensor([-0.0006,  0.0035])\n",
      "\tparams: tensor([  5.3641, -17.2841])\n",
      "Epoch: 3968,Loss: 2.927683\n",
      "\tgrad: tensor([-0.0006,  0.0035])\n",
      "\tparams: tensor([  5.3641, -17.2842])\n",
      "Epoch: 3969,Loss: 2.927683\n",
      "\tgrad: tensor([-0.0006,  0.0035])\n",
      "\tparams: tensor([  5.3641, -17.2842])\n",
      "Epoch: 3970,Loss: 2.927682\n",
      "\tgrad: tensor([-0.0006,  0.0035])\n",
      "\tparams: tensor([  5.3641, -17.2842])\n",
      "Epoch: 3971,Loss: 2.927683\n",
      "\tgrad: tensor([-0.0006,  0.0035])\n",
      "\tparams: tensor([  5.3641, -17.2843])\n",
      "Epoch: 3972,Loss: 2.927684\n",
      "\tgrad: tensor([-0.0006,  0.0035])\n",
      "\tparams: tensor([  5.3641, -17.2843])\n",
      "Epoch: 3973,Loss: 2.927682\n",
      "\tgrad: tensor([-0.0006,  0.0035])\n",
      "\tparams: tensor([  5.3641, -17.2843])\n",
      "Epoch: 3974,Loss: 2.927683\n",
      "\tgrad: tensor([-0.0006,  0.0035])\n",
      "\tparams: tensor([  5.3641, -17.2844])\n",
      "Epoch: 3975,Loss: 2.927683\n",
      "\tgrad: tensor([-0.0006,  0.0035])\n",
      "\tparams: tensor([  5.3641, -17.2844])\n",
      "Epoch: 3976,Loss: 2.927683\n",
      "\tgrad: tensor([-0.0006,  0.0035])\n",
      "\tparams: tensor([  5.3641, -17.2844])\n",
      "Epoch: 3977,Loss: 2.927682\n",
      "\tgrad: tensor([-0.0006,  0.0035])\n",
      "\tparams: tensor([  5.3641, -17.2845])\n",
      "Epoch: 3978,Loss: 2.927682\n",
      "\tgrad: tensor([-0.0006,  0.0035])\n",
      "\tparams: tensor([  5.3641, -17.2845])\n",
      "Epoch: 3979,Loss: 2.927682\n",
      "\tgrad: tensor([-0.0006,  0.0034])\n",
      "\tparams: tensor([  5.3641, -17.2845])\n",
      "Epoch: 3980,Loss: 2.927681\n",
      "\tgrad: tensor([-0.0006,  0.0034])\n",
      "\tparams: tensor([  5.3642, -17.2846])\n",
      "Epoch: 3981,Loss: 2.927682\n",
      "\tgrad: tensor([-0.0006,  0.0034])\n",
      "\tparams: tensor([  5.3642, -17.2846])\n",
      "Epoch: 3982,Loss: 2.927682\n",
      "\tgrad: tensor([-0.0006,  0.0034])\n",
      "\tparams: tensor([  5.3642, -17.2847])\n",
      "Epoch: 3983,Loss: 2.927682\n",
      "\tgrad: tensor([-0.0006,  0.0034])\n",
      "\tparams: tensor([  5.3642, -17.2847])\n",
      "Epoch: 3984,Loss: 2.927682\n",
      "\tgrad: tensor([-0.0006,  0.0034])\n",
      "\tparams: tensor([  5.3642, -17.2847])\n",
      "Epoch: 3985,Loss: 2.927682\n",
      "\tgrad: tensor([-0.0006,  0.0034])\n",
      "\tparams: tensor([  5.3642, -17.2848])\n",
      "Epoch: 3986,Loss: 2.927682\n",
      "\tgrad: tensor([-0.0006,  0.0034])\n",
      "\tparams: tensor([  5.3642, -17.2848])\n",
      "Epoch: 3987,Loss: 2.927680\n",
      "\tgrad: tensor([-0.0006,  0.0034])\n",
      "\tparams: tensor([  5.3642, -17.2848])\n",
      "Epoch: 3988,Loss: 2.927682\n",
      "\tgrad: tensor([-0.0006,  0.0034])\n",
      "\tparams: tensor([  5.3642, -17.2849])\n",
      "Epoch: 3989,Loss: 2.927681\n",
      "\tgrad: tensor([-0.0006,  0.0034])\n",
      "\tparams: tensor([  5.3642, -17.2849])\n",
      "Epoch: 3990,Loss: 2.927681\n",
      "\tgrad: tensor([-0.0006,  0.0034])\n",
      "\tparams: tensor([  5.3642, -17.2849])\n",
      "Epoch: 3991,Loss: 2.927680\n",
      "\tgrad: tensor([-0.0006,  0.0034])\n",
      "\tparams: tensor([  5.3642, -17.2850])\n",
      "Epoch: 3992,Loss: 2.927681\n",
      "\tgrad: tensor([-0.0006,  0.0034])\n",
      "\tparams: tensor([  5.3642, -17.2850])\n",
      "Epoch: 3993,Loss: 2.927680\n",
      "\tgrad: tensor([-0.0006,  0.0034])\n",
      "\tparams: tensor([  5.3642, -17.2850])\n",
      "Epoch: 3994,Loss: 2.927680\n",
      "\tgrad: tensor([-0.0006,  0.0034])\n",
      "\tparams: tensor([  5.3642, -17.2851])\n",
      "Epoch: 3995,Loss: 2.927681\n",
      "\tgrad: tensor([-0.0006,  0.0033])\n",
      "\tparams: tensor([  5.3642, -17.2851])\n",
      "Epoch: 3996,Loss: 2.927681\n",
      "\tgrad: tensor([-0.0006,  0.0033])\n",
      "\tparams: tensor([  5.3642, -17.2851])\n",
      "Epoch: 3997,Loss: 2.927679\n",
      "\tgrad: tensor([-0.0006,  0.0033])\n",
      "\tparams: tensor([  5.3643, -17.2852])\n",
      "Epoch: 3998,Loss: 2.927680\n",
      "\tgrad: tensor([-0.0006,  0.0033])\n",
      "\tparams: tensor([  5.3643, -17.2852])\n",
      "Epoch: 3999,Loss: 2.927679\n",
      "\tgrad: tensor([-0.0006,  0.0033])\n",
      "\tparams: tensor([  5.3643, -17.2852])\n",
      "Epoch: 4000,Loss: 2.927680\n",
      "\tgrad: tensor([-0.0006,  0.0033])\n",
      "\tparams: tensor([  5.3643, -17.2853])\n",
      "Epoch: 4001,Loss: 2.927680\n",
      "\tgrad: tensor([-0.0006,  0.0033])\n",
      "\tparams: tensor([  5.3643, -17.2853])\n",
      "Epoch: 4002,Loss: 2.927681\n",
      "\tgrad: tensor([-0.0006,  0.0033])\n",
      "\tparams: tensor([  5.3643, -17.2853])\n",
      "Epoch: 4003,Loss: 2.927679\n",
      "\tgrad: tensor([-0.0006,  0.0033])\n",
      "\tparams: tensor([  5.3643, -17.2854])\n",
      "Epoch: 4004,Loss: 2.927679\n",
      "\tgrad: tensor([-0.0006,  0.0033])\n",
      "\tparams: tensor([  5.3643, -17.2854])\n",
      "Epoch: 4005,Loss: 2.927680\n",
      "\tgrad: tensor([-0.0006,  0.0033])\n",
      "\tparams: tensor([  5.3643, -17.2854])\n",
      "Epoch: 4006,Loss: 2.927680\n",
      "\tgrad: tensor([-0.0006,  0.0033])\n",
      "\tparams: tensor([  5.3643, -17.2855])\n",
      "Epoch: 4007,Loss: 2.927677\n",
      "\tgrad: tensor([-0.0006,  0.0033])\n",
      "\tparams: tensor([  5.3643, -17.2855])\n",
      "Epoch: 4008,Loss: 2.927678\n",
      "\tgrad: tensor([-0.0006,  0.0033])\n",
      "\tparams: tensor([  5.3643, -17.2855])\n",
      "Epoch: 4009,Loss: 2.927679\n",
      "\tgrad: tensor([-0.0006,  0.0033])\n",
      "\tparams: tensor([  5.3643, -17.2856])\n",
      "Epoch: 4010,Loss: 2.927678\n",
      "\tgrad: tensor([-0.0006,  0.0033])\n",
      "\tparams: tensor([  5.3643, -17.2856])\n",
      "Epoch: 4011,Loss: 2.927679\n",
      "\tgrad: tensor([-0.0006,  0.0033])\n",
      "\tparams: tensor([  5.3643, -17.2856])\n",
      "Epoch: 4012,Loss: 2.927679\n",
      "\tgrad: tensor([-0.0006,  0.0033])\n",
      "\tparams: tensor([  5.3643, -17.2857])\n",
      "Epoch: 4013,Loss: 2.927679\n",
      "\tgrad: tensor([-0.0006,  0.0032])\n",
      "\tparams: tensor([  5.3643, -17.2857])\n",
      "Epoch: 4014,Loss: 2.927677\n",
      "\tgrad: tensor([-0.0006,  0.0032])\n",
      "\tparams: tensor([  5.3644, -17.2857])\n",
      "Epoch: 4015,Loss: 2.927677\n",
      "\tgrad: tensor([-0.0006,  0.0032])\n",
      "\tparams: tensor([  5.3644, -17.2857])\n",
      "Epoch: 4016,Loss: 2.927677\n",
      "\tgrad: tensor([-0.0006,  0.0032])\n",
      "\tparams: tensor([  5.3644, -17.2858])\n",
      "Epoch: 4017,Loss: 2.927679\n",
      "\tgrad: tensor([-0.0006,  0.0032])\n",
      "\tparams: tensor([  5.3644, -17.2858])\n",
      "Epoch: 4018,Loss: 2.927677\n",
      "\tgrad: tensor([-0.0006,  0.0032])\n",
      "\tparams: tensor([  5.3644, -17.2858])\n",
      "Epoch: 4019,Loss: 2.927678\n",
      "\tgrad: tensor([-0.0006,  0.0032])\n",
      "\tparams: tensor([  5.3644, -17.2859])\n",
      "Epoch: 4020,Loss: 2.927678\n",
      "\tgrad: tensor([-0.0006,  0.0032])\n",
      "\tparams: tensor([  5.3644, -17.2859])\n",
      "Epoch: 4021,Loss: 2.927677\n",
      "\tgrad: tensor([-0.0006,  0.0032])\n",
      "\tparams: tensor([  5.3644, -17.2859])\n",
      "Epoch: 4022,Loss: 2.927677\n",
      "\tgrad: tensor([-0.0006,  0.0032])\n",
      "\tparams: tensor([  5.3644, -17.2860])\n",
      "Epoch: 4023,Loss: 2.927678\n",
      "\tgrad: tensor([-0.0006,  0.0032])\n",
      "\tparams: tensor([  5.3644, -17.2860])\n",
      "Epoch: 4024,Loss: 2.927677\n",
      "\tgrad: tensor([-0.0006,  0.0032])\n",
      "\tparams: tensor([  5.3644, -17.2860])\n",
      "Epoch: 4025,Loss: 2.927677\n",
      "\tgrad: tensor([-0.0006,  0.0032])\n",
      "\tparams: tensor([  5.3644, -17.2861])\n",
      "Epoch: 4026,Loss: 2.927676\n",
      "\tgrad: tensor([-0.0006,  0.0032])\n",
      "\tparams: tensor([  5.3644, -17.2861])\n",
      "Epoch: 4027,Loss: 2.927676\n",
      "\tgrad: tensor([-0.0006,  0.0032])\n",
      "\tparams: tensor([  5.3644, -17.2861])\n",
      "Epoch: 4028,Loss: 2.927675\n",
      "\tgrad: tensor([-0.0006,  0.0032])\n",
      "\tparams: tensor([  5.3644, -17.2862])\n",
      "Epoch: 4029,Loss: 2.927677\n",
      "\tgrad: tensor([-0.0006,  0.0032])\n",
      "\tparams: tensor([  5.3644, -17.2862])\n",
      "Epoch: 4030,Loss: 2.927674\n",
      "\tgrad: tensor([-0.0006,  0.0032])\n",
      "\tparams: tensor([  5.3644, -17.2862])\n",
      "Epoch: 4031,Loss: 2.927676\n",
      "\tgrad: tensor([-0.0006,  0.0031])\n",
      "\tparams: tensor([  5.3644, -17.2863])\n",
      "Epoch: 4032,Loss: 2.927675\n",
      "\tgrad: tensor([-0.0006,  0.0031])\n",
      "\tparams: tensor([  5.3645, -17.2863])\n",
      "Epoch: 4033,Loss: 2.927675\n",
      "\tgrad: tensor([-0.0006,  0.0031])\n",
      "\tparams: tensor([  5.3645, -17.2863])\n",
      "Epoch: 4034,Loss: 2.927675\n",
      "\tgrad: tensor([-0.0005,  0.0031])\n",
      "\tparams: tensor([  5.3645, -17.2864])\n",
      "Epoch: 4035,Loss: 2.927675\n",
      "\tgrad: tensor([-0.0005,  0.0031])\n",
      "\tparams: tensor([  5.3645, -17.2864])\n",
      "Epoch: 4036,Loss: 2.927674\n",
      "\tgrad: tensor([-0.0005,  0.0031])\n",
      "\tparams: tensor([  5.3645, -17.2864])\n",
      "Epoch: 4037,Loss: 2.927674\n",
      "\tgrad: tensor([-0.0006,  0.0031])\n",
      "\tparams: tensor([  5.3645, -17.2865])\n",
      "Epoch: 4038,Loss: 2.927677\n",
      "\tgrad: tensor([-0.0005,  0.0031])\n",
      "\tparams: tensor([  5.3645, -17.2865])\n",
      "Epoch: 4039,Loss: 2.927674\n",
      "\tgrad: tensor([-0.0005,  0.0031])\n",
      "\tparams: tensor([  5.3645, -17.2865])\n",
      "Epoch: 4040,Loss: 2.927676\n",
      "\tgrad: tensor([-0.0005,  0.0031])\n",
      "\tparams: tensor([  5.3645, -17.2865])\n",
      "Epoch: 4041,Loss: 2.927675\n",
      "\tgrad: tensor([-0.0006,  0.0031])\n",
      "\tparams: tensor([  5.3645, -17.2866])\n",
      "Epoch: 4042,Loss: 2.927675\n",
      "\tgrad: tensor([-0.0005,  0.0031])\n",
      "\tparams: tensor([  5.3645, -17.2866])\n",
      "Epoch: 4043,Loss: 2.927675\n",
      "\tgrad: tensor([-0.0005,  0.0031])\n",
      "\tparams: tensor([  5.3645, -17.2866])\n",
      "Epoch: 4044,Loss: 2.927674\n",
      "\tgrad: tensor([-0.0005,  0.0031])\n",
      "\tparams: tensor([  5.3645, -17.2867])\n",
      "Epoch: 4045,Loss: 2.927674\n",
      "\tgrad: tensor([-0.0006,  0.0031])\n",
      "\tparams: tensor([  5.3645, -17.2867])\n",
      "Epoch: 4046,Loss: 2.927675\n",
      "\tgrad: tensor([-0.0005,  0.0031])\n",
      "\tparams: tensor([  5.3645, -17.2867])\n",
      "Epoch: 4047,Loss: 2.927674\n",
      "\tgrad: tensor([-0.0005,  0.0031])\n",
      "\tparams: tensor([  5.3645, -17.2868])\n",
      "Epoch: 4048,Loss: 2.927674\n",
      "\tgrad: tensor([-0.0006,  0.0031])\n",
      "\tparams: tensor([  5.3645, -17.2868])\n",
      "Epoch: 4049,Loss: 2.927675\n",
      "\tgrad: tensor([-0.0005,  0.0031])\n",
      "\tparams: tensor([  5.3645, -17.2868])\n",
      "Epoch: 4050,Loss: 2.927672\n",
      "\tgrad: tensor([-0.0005,  0.0031])\n",
      "\tparams: tensor([  5.3646, -17.2868])\n",
      "Epoch: 4051,Loss: 2.927675\n",
      "\tgrad: tensor([-0.0005,  0.0030])\n",
      "\tparams: tensor([  5.3646, -17.2869])\n",
      "Epoch: 4052,Loss: 2.927675\n",
      "\tgrad: tensor([-0.0006,  0.0030])\n",
      "\tparams: tensor([  5.3646, -17.2869])\n",
      "Epoch: 4053,Loss: 2.927673\n",
      "\tgrad: tensor([-0.0005,  0.0030])\n",
      "\tparams: tensor([  5.3646, -17.2869])\n",
      "Epoch: 4054,Loss: 2.927673\n",
      "\tgrad: tensor([-0.0005,  0.0030])\n",
      "\tparams: tensor([  5.3646, -17.2870])\n",
      "Epoch: 4055,Loss: 2.927674\n",
      "\tgrad: tensor([-0.0005,  0.0030])\n",
      "\tparams: tensor([  5.3646, -17.2870])\n",
      "Epoch: 4056,Loss: 2.927673\n",
      "\tgrad: tensor([-0.0006,  0.0030])\n",
      "\tparams: tensor([  5.3646, -17.2870])\n",
      "Epoch: 4057,Loss: 2.927674\n",
      "\tgrad: tensor([-0.0005,  0.0030])\n",
      "\tparams: tensor([  5.3646, -17.2871])\n",
      "Epoch: 4058,Loss: 2.927672\n",
      "\tgrad: tensor([-0.0005,  0.0030])\n",
      "\tparams: tensor([  5.3646, -17.2871])\n",
      "Epoch: 4059,Loss: 2.927674\n",
      "\tgrad: tensor([-0.0006,  0.0030])\n",
      "\tparams: tensor([  5.3646, -17.2871])\n",
      "Epoch: 4060,Loss: 2.927675\n",
      "\tgrad: tensor([-0.0005,  0.0030])\n",
      "\tparams: tensor([  5.3646, -17.2872])\n",
      "Epoch: 4061,Loss: 2.927672\n",
      "\tgrad: tensor([-0.0005,  0.0030])\n",
      "\tparams: tensor([  5.3646, -17.2872])\n",
      "Epoch: 4062,Loss: 2.927673\n",
      "\tgrad: tensor([-0.0005,  0.0030])\n",
      "\tparams: tensor([  5.3646, -17.2872])\n",
      "Epoch: 4063,Loss: 2.927675\n",
      "\tgrad: tensor([-0.0006,  0.0030])\n",
      "\tparams: tensor([  5.3646, -17.2872])\n",
      "Epoch: 4064,Loss: 2.927673\n",
      "\tgrad: tensor([-0.0005,  0.0030])\n",
      "\tparams: tensor([  5.3646, -17.2873])\n",
      "Epoch: 4065,Loss: 2.927674\n",
      "\tgrad: tensor([-0.0005,  0.0030])\n",
      "\tparams: tensor([  5.3646, -17.2873])\n",
      "Epoch: 4066,Loss: 2.927672\n",
      "\tgrad: tensor([-0.0005,  0.0030])\n",
      "\tparams: tensor([  5.3646, -17.2873])\n",
      "Epoch: 4067,Loss: 2.927673\n",
      "\tgrad: tensor([-0.0005,  0.0030])\n",
      "\tparams: tensor([  5.3646, -17.2874])\n",
      "Epoch: 4068,Loss: 2.927673\n",
      "\tgrad: tensor([-0.0005,  0.0030])\n",
      "\tparams: tensor([  5.3646, -17.2874])\n",
      "Epoch: 4069,Loss: 2.927672\n",
      "\tgrad: tensor([-0.0005,  0.0030])\n",
      "\tparams: tensor([  5.3647, -17.2874])\n",
      "Epoch: 4070,Loss: 2.927672\n",
      "\tgrad: tensor([-0.0005,  0.0030])\n",
      "\tparams: tensor([  5.3647, -17.2875])\n",
      "Epoch: 4071,Loss: 2.927673\n",
      "\tgrad: tensor([-0.0005,  0.0029])\n",
      "\tparams: tensor([  5.3647, -17.2875])\n",
      "Epoch: 4072,Loss: 2.927673\n",
      "\tgrad: tensor([-0.0005,  0.0029])\n",
      "\tparams: tensor([  5.3647, -17.2875])\n",
      "Epoch: 4073,Loss: 2.927671\n",
      "\tgrad: tensor([-0.0005,  0.0029])\n",
      "\tparams: tensor([  5.3647, -17.2875])\n",
      "Epoch: 4074,Loss: 2.927673\n",
      "\tgrad: tensor([-0.0005,  0.0029])\n",
      "\tparams: tensor([  5.3647, -17.2876])\n",
      "Epoch: 4075,Loss: 2.927672\n",
      "\tgrad: tensor([-0.0005,  0.0029])\n",
      "\tparams: tensor([  5.3647, -17.2876])\n",
      "Epoch: 4076,Loss: 2.927672\n",
      "\tgrad: tensor([-0.0005,  0.0029])\n",
      "\tparams: tensor([  5.3647, -17.2876])\n",
      "Epoch: 4077,Loss: 2.927672\n",
      "\tgrad: tensor([-0.0005,  0.0029])\n",
      "\tparams: tensor([  5.3647, -17.2877])\n",
      "Epoch: 4078,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0029])\n",
      "\tparams: tensor([  5.3647, -17.2877])\n",
      "Epoch: 4079,Loss: 2.927672\n",
      "\tgrad: tensor([-0.0005,  0.0029])\n",
      "\tparams: tensor([  5.3647, -17.2877])\n",
      "Epoch: 4080,Loss: 2.927672\n",
      "\tgrad: tensor([-0.0005,  0.0029])\n",
      "\tparams: tensor([  5.3647, -17.2877])\n",
      "Epoch: 4081,Loss: 2.927671\n",
      "\tgrad: tensor([-0.0005,  0.0029])\n",
      "\tparams: tensor([  5.3647, -17.2878])\n",
      "Epoch: 4082,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0029])\n",
      "\tparams: tensor([  5.3647, -17.2878])\n",
      "Epoch: 4083,Loss: 2.927673\n",
      "\tgrad: tensor([-0.0005,  0.0029])\n",
      "\tparams: tensor([  5.3647, -17.2878])\n",
      "Epoch: 4084,Loss: 2.927672\n",
      "\tgrad: tensor([-0.0005,  0.0029])\n",
      "\tparams: tensor([  5.3647, -17.2879])\n",
      "Epoch: 4085,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0029])\n",
      "\tparams: tensor([  5.3647, -17.2879])\n",
      "Epoch: 4086,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0029])\n",
      "\tparams: tensor([  5.3647, -17.2879])\n",
      "Epoch: 4087,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0029])\n",
      "\tparams: tensor([  5.3647, -17.2879])\n",
      "Epoch: 4088,Loss: 2.927672\n",
      "\tgrad: tensor([-0.0005,  0.0029])\n",
      "\tparams: tensor([  5.3647, -17.2880])\n",
      "Epoch: 4089,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0029])\n",
      "\tparams: tensor([  5.3648, -17.2880])\n",
      "Epoch: 4090,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0029])\n",
      "\tparams: tensor([  5.3648, -17.2880])\n",
      "Epoch: 4091,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0028])\n",
      "\tparams: tensor([  5.3648, -17.2881])\n",
      "Epoch: 4092,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0028])\n",
      "\tparams: tensor([  5.3648, -17.2881])\n",
      "Epoch: 4093,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0028])\n",
      "\tparams: tensor([  5.3648, -17.2881])\n",
      "Epoch: 4094,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0028])\n",
      "\tparams: tensor([  5.3648, -17.2881])\n",
      "Epoch: 4095,Loss: 2.927669\n",
      "\tgrad: tensor([-0.0005,  0.0028])\n",
      "\tparams: tensor([  5.3648, -17.2882])\n",
      "Epoch: 4096,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0028])\n",
      "\tparams: tensor([  5.3648, -17.2882])\n",
      "Epoch: 4097,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0028])\n",
      "\tparams: tensor([  5.3648, -17.2882])\n",
      "Epoch: 4098,Loss: 2.927671\n",
      "\tgrad: tensor([-0.0005,  0.0028])\n",
      "\tparams: tensor([  5.3648, -17.2883])\n",
      "Epoch: 4099,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0028])\n",
      "\tparams: tensor([  5.3648, -17.2883])\n",
      "Epoch: 4100,Loss: 2.927671\n",
      "\tgrad: tensor([-0.0005,  0.0028])\n",
      "\tparams: tensor([  5.3648, -17.2883])\n",
      "Epoch: 4101,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0028])\n",
      "\tparams: tensor([  5.3648, -17.2883])\n",
      "Epoch: 4102,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0028])\n",
      "\tparams: tensor([  5.3648, -17.2884])\n",
      "Epoch: 4103,Loss: 2.927671\n",
      "\tgrad: tensor([-0.0005,  0.0028])\n",
      "\tparams: tensor([  5.3648, -17.2884])\n",
      "Epoch: 4104,Loss: 2.927669\n",
      "\tgrad: tensor([-0.0005,  0.0028])\n",
      "\tparams: tensor([  5.3648, -17.2884])\n",
      "Epoch: 4105,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0028])\n",
      "\tparams: tensor([  5.3648, -17.2885])\n",
      "Epoch: 4106,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0028])\n",
      "\tparams: tensor([  5.3648, -17.2885])\n",
      "Epoch: 4107,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0028])\n",
      "\tparams: tensor([  5.3648, -17.2885])\n",
      "Epoch: 4108,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0028])\n",
      "\tparams: tensor([  5.3648, -17.2885])\n",
      "Epoch: 4109,Loss: 2.927668\n",
      "\tgrad: tensor([-0.0005,  0.0028])\n",
      "\tparams: tensor([  5.3649, -17.2886])\n",
      "Epoch: 4110,Loss: 2.927669\n",
      "\tgrad: tensor([-0.0005,  0.0028])\n",
      "\tparams: tensor([  5.3649, -17.2886])\n",
      "Epoch: 4111,Loss: 2.927669\n",
      "\tgrad: tensor([-0.0005,  0.0028])\n",
      "\tparams: tensor([  5.3649, -17.2886])\n",
      "Epoch: 4112,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0027])\n",
      "\tparams: tensor([  5.3649, -17.2886])\n",
      "Epoch: 4113,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0027])\n",
      "\tparams: tensor([  5.3649, -17.2887])\n",
      "Epoch: 4114,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0027])\n",
      "\tparams: tensor([  5.3649, -17.2887])\n",
      "Epoch: 4115,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0027])\n",
      "\tparams: tensor([  5.3649, -17.2887])\n",
      "Epoch: 4116,Loss: 2.927669\n",
      "\tgrad: tensor([-0.0005,  0.0027])\n",
      "\tparams: tensor([  5.3649, -17.2887])\n",
      "Epoch: 4117,Loss: 2.927669\n",
      "\tgrad: tensor([-0.0004,  0.0027])\n",
      "\tparams: tensor([  5.3649, -17.2888])\n",
      "Epoch: 4118,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0027])\n",
      "\tparams: tensor([  5.3649, -17.2888])\n",
      "Epoch: 4119,Loss: 2.927669\n",
      "\tgrad: tensor([-0.0005,  0.0027])\n",
      "\tparams: tensor([  5.3649, -17.2888])\n",
      "Epoch: 4120,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0027])\n",
      "\tparams: tensor([  5.3649, -17.2889])\n",
      "Epoch: 4121,Loss: 2.927668\n",
      "\tgrad: tensor([-0.0005,  0.0027])\n",
      "\tparams: tensor([  5.3649, -17.2889])\n",
      "Epoch: 4122,Loss: 2.927668\n",
      "\tgrad: tensor([-0.0005,  0.0027])\n",
      "\tparams: tensor([  5.3649, -17.2889])\n",
      "Epoch: 4123,Loss: 2.927669\n",
      "\tgrad: tensor([-0.0005,  0.0027])\n",
      "\tparams: tensor([  5.3649, -17.2889])\n",
      "Epoch: 4124,Loss: 2.927668\n",
      "\tgrad: tensor([-0.0005,  0.0027])\n",
      "\tparams: tensor([  5.3649, -17.2890])\n",
      "Epoch: 4125,Loss: 2.927670\n",
      "\tgrad: tensor([-0.0005,  0.0027])\n",
      "\tparams: tensor([  5.3649, -17.2890])\n",
      "Epoch: 4126,Loss: 2.927666\n",
      "\tgrad: tensor([-0.0005,  0.0027])\n",
      "\tparams: tensor([  5.3649, -17.2890])\n",
      "Epoch: 4127,Loss: 2.927669\n",
      "\tgrad: tensor([-0.0005,  0.0027])\n",
      "\tparams: tensor([  5.3649, -17.2890])\n",
      "Epoch: 4128,Loss: 2.927668\n",
      "\tgrad: tensor([-0.0005,  0.0027])\n",
      "\tparams: tensor([  5.3649, -17.2891])\n",
      "Epoch: 4129,Loss: 2.927669\n",
      "\tgrad: tensor([-0.0005,  0.0027])\n",
      "\tparams: tensor([  5.3649, -17.2891])\n",
      "Epoch: 4130,Loss: 2.927667\n",
      "\tgrad: tensor([-0.0005,  0.0027])\n",
      "\tparams: tensor([  5.3650, -17.2891])\n",
      "Epoch: 4131,Loss: 2.927667\n",
      "\tgrad: tensor([-0.0004,  0.0027])\n",
      "\tparams: tensor([  5.3650, -17.2892])\n",
      "Epoch: 4132,Loss: 2.927668\n",
      "\tgrad: tensor([-0.0005,  0.0027])\n",
      "\tparams: tensor([  5.3650, -17.2892])\n",
      "Epoch: 4133,Loss: 2.927667\n",
      "\tgrad: tensor([-0.0005,  0.0027])\n",
      "\tparams: tensor([  5.3650, -17.2892])\n",
      "Epoch: 4134,Loss: 2.927667\n",
      "\tgrad: tensor([-0.0005,  0.0026])\n",
      "\tparams: tensor([  5.3650, -17.2892])\n",
      "Epoch: 4135,Loss: 2.927666\n",
      "\tgrad: tensor([-0.0005,  0.0026])\n",
      "\tparams: tensor([  5.3650, -17.2893])\n",
      "Epoch: 4136,Loss: 2.927666\n",
      "\tgrad: tensor([-0.0005,  0.0026])\n",
      "\tparams: tensor([  5.3650, -17.2893])\n",
      "Epoch: 4137,Loss: 2.927669\n",
      "\tgrad: tensor([-0.0005,  0.0026])\n",
      "\tparams: tensor([  5.3650, -17.2893])\n",
      "Epoch: 4138,Loss: 2.927666\n",
      "\tgrad: tensor([-0.0004,  0.0026])\n",
      "\tparams: tensor([  5.3650, -17.2893])\n",
      "Epoch: 4139,Loss: 2.927668\n",
      "\tgrad: tensor([-0.0005,  0.0026])\n",
      "\tparams: tensor([  5.3650, -17.2894])\n",
      "Epoch: 4140,Loss: 2.927666\n",
      "\tgrad: tensor([-0.0005,  0.0026])\n",
      "\tparams: tensor([  5.3650, -17.2894])\n",
      "Epoch: 4141,Loss: 2.927667\n",
      "\tgrad: tensor([-0.0005,  0.0026])\n",
      "\tparams: tensor([  5.3650, -17.2894])\n",
      "Epoch: 4142,Loss: 2.927667\n",
      "\tgrad: tensor([-0.0005,  0.0026])\n",
      "\tparams: tensor([  5.3650, -17.2894])\n",
      "Epoch: 4143,Loss: 2.927666\n",
      "\tgrad: tensor([-0.0005,  0.0026])\n",
      "\tparams: tensor([  5.3650, -17.2895])\n",
      "Epoch: 4144,Loss: 2.927667\n",
      "\tgrad: tensor([-0.0005,  0.0026])\n",
      "\tparams: tensor([  5.3650, -17.2895])\n",
      "Epoch: 4145,Loss: 2.927666\n",
      "\tgrad: tensor([-0.0005,  0.0026])\n",
      "\tparams: tensor([  5.3650, -17.2895])\n",
      "Epoch: 4146,Loss: 2.927667\n",
      "\tgrad: tensor([-0.0005,  0.0026])\n",
      "\tparams: tensor([  5.3650, -17.2896])\n",
      "Epoch: 4147,Loss: 2.927667\n",
      "\tgrad: tensor([-0.0005,  0.0026])\n",
      "\tparams: tensor([  5.3650, -17.2896])\n",
      "Epoch: 4148,Loss: 2.927667\n",
      "\tgrad: tensor([-0.0005,  0.0026])\n",
      "\tparams: tensor([  5.3650, -17.2896])\n",
      "Epoch: 4149,Loss: 2.927667\n",
      "\tgrad: tensor([-0.0005,  0.0026])\n",
      "\tparams: tensor([  5.3650, -17.2896])\n",
      "Epoch: 4150,Loss: 2.927665\n",
      "\tgrad: tensor([-0.0005,  0.0026])\n",
      "\tparams: tensor([  5.3650, -17.2897])\n",
      "Epoch: 4151,Loss: 2.927666\n",
      "\tgrad: tensor([-0.0004,  0.0026])\n",
      "\tparams: tensor([  5.3651, -17.2897])\n",
      "Epoch: 4152,Loss: 2.927666\n",
      "\tgrad: tensor([-0.0004,  0.0026])\n",
      "\tparams: tensor([  5.3651, -17.2897])\n",
      "Epoch: 4153,Loss: 2.927666\n",
      "\tgrad: tensor([-0.0005,  0.0026])\n",
      "\tparams: tensor([  5.3651, -17.2897])\n",
      "Epoch: 4154,Loss: 2.927666\n",
      "\tgrad: tensor([-0.0005,  0.0026])\n",
      "\tparams: tensor([  5.3651, -17.2898])\n",
      "Epoch: 4155,Loss: 2.927666\n",
      "\tgrad: tensor([-0.0004,  0.0026])\n",
      "\tparams: tensor([  5.3651, -17.2898])\n",
      "Epoch: 4156,Loss: 2.927666\n",
      "\tgrad: tensor([-0.0004,  0.0026])\n",
      "\tparams: tensor([  5.3651, -17.2898])\n",
      "Epoch: 4157,Loss: 2.927666\n",
      "\tgrad: tensor([-0.0004,  0.0025])\n",
      "\tparams: tensor([  5.3651, -17.2898])\n",
      "Epoch: 4158,Loss: 2.927665\n",
      "\tgrad: tensor([-0.0004,  0.0025])\n",
      "\tparams: tensor([  5.3651, -17.2899])\n",
      "Epoch: 4159,Loss: 2.927666\n",
      "\tgrad: tensor([-0.0004,  0.0025])\n",
      "\tparams: tensor([  5.3651, -17.2899])\n",
      "Epoch: 4160,Loss: 2.927665\n",
      "\tgrad: tensor([-0.0004,  0.0025])\n",
      "\tparams: tensor([  5.3651, -17.2899])\n",
      "Epoch: 4161,Loss: 2.927664\n",
      "\tgrad: tensor([-0.0005,  0.0025])\n",
      "\tparams: tensor([  5.3651, -17.2899])\n",
      "Epoch: 4162,Loss: 2.927666\n",
      "\tgrad: tensor([-0.0004,  0.0025])\n",
      "\tparams: tensor([  5.3651, -17.2900])\n",
      "Epoch: 4163,Loss: 2.927665\n",
      "\tgrad: tensor([-0.0004,  0.0025])\n",
      "\tparams: tensor([  5.3651, -17.2900])\n",
      "Epoch: 4164,Loss: 2.927666\n",
      "\tgrad: tensor([-0.0004,  0.0025])\n",
      "\tparams: tensor([  5.3651, -17.2900])\n",
      "Epoch: 4165,Loss: 2.927664\n",
      "\tgrad: tensor([-0.0004,  0.0025])\n",
      "\tparams: tensor([  5.3651, -17.2900])\n",
      "Epoch: 4166,Loss: 2.927665\n",
      "\tgrad: tensor([-0.0004,  0.0025])\n",
      "\tparams: tensor([  5.3651, -17.2901])\n",
      "Epoch: 4167,Loss: 2.927665\n",
      "\tgrad: tensor([-0.0005,  0.0025])\n",
      "\tparams: tensor([  5.3651, -17.2901])\n",
      "Epoch: 4168,Loss: 2.927665\n",
      "\tgrad: tensor([-0.0004,  0.0025])\n",
      "\tparams: tensor([  5.3651, -17.2901])\n",
      "Epoch: 4169,Loss: 2.927666\n",
      "\tgrad: tensor([-0.0004,  0.0025])\n",
      "\tparams: tensor([  5.3651, -17.2901])\n",
      "Epoch: 4170,Loss: 2.927664\n",
      "\tgrad: tensor([-0.0004,  0.0025])\n",
      "\tparams: tensor([  5.3651, -17.2902])\n",
      "Epoch: 4171,Loss: 2.927665\n",
      "\tgrad: tensor([-0.0004,  0.0025])\n",
      "\tparams: tensor([  5.3651, -17.2902])\n",
      "Epoch: 4172,Loss: 2.927666\n",
      "\tgrad: tensor([-0.0004,  0.0025])\n",
      "\tparams: tensor([  5.3651, -17.2902])\n",
      "Epoch: 4173,Loss: 2.927663\n",
      "\tgrad: tensor([-0.0005,  0.0025])\n",
      "\tparams: tensor([  5.3651, -17.2902])\n",
      "Epoch: 4174,Loss: 2.927664\n",
      "\tgrad: tensor([-0.0004,  0.0025])\n",
      "\tparams: tensor([  5.3652, -17.2903])\n",
      "Epoch: 4175,Loss: 2.927664\n",
      "\tgrad: tensor([-0.0004,  0.0025])\n",
      "\tparams: tensor([  5.3652, -17.2903])\n",
      "Epoch: 4176,Loss: 2.927665\n",
      "\tgrad: tensor([-0.0004,  0.0025])\n",
      "\tparams: tensor([  5.3652, -17.2903])\n",
      "Epoch: 4177,Loss: 2.927663\n",
      "\tgrad: tensor([-0.0004,  0.0025])\n",
      "\tparams: tensor([  5.3652, -17.2903])\n",
      "Epoch: 4178,Loss: 2.927664\n",
      "\tgrad: tensor([-0.0005,  0.0025])\n",
      "\tparams: tensor([  5.3652, -17.2903])\n",
      "Epoch: 4179,Loss: 2.927664\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3652, -17.2904])\n",
      "Epoch: 4180,Loss: 2.927663\n",
      "\tgrad: tensor([-0.0005,  0.0024])\n",
      "\tparams: tensor([  5.3652, -17.2904])\n",
      "Epoch: 4181,Loss: 2.927664\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3652, -17.2904])\n",
      "Epoch: 4182,Loss: 2.927664\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3652, -17.2904])\n",
      "Epoch: 4183,Loss: 2.927663\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3652, -17.2905])\n",
      "Epoch: 4184,Loss: 2.927664\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3652, -17.2905])\n",
      "Epoch: 4185,Loss: 2.927664\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3652, -17.2905])\n",
      "Epoch: 4186,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0005,  0.0024])\n",
      "\tparams: tensor([  5.3652, -17.2905])\n",
      "Epoch: 4187,Loss: 2.927665\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3652, -17.2906])\n",
      "Epoch: 4188,Loss: 2.927663\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3652, -17.2906])\n",
      "Epoch: 4189,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3652, -17.2906])\n",
      "Epoch: 4190,Loss: 2.927663\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3652, -17.2906])\n",
      "Epoch: 4191,Loss: 2.927664\n",
      "\tgrad: tensor([-0.0005,  0.0024])\n",
      "\tparams: tensor([  5.3652, -17.2907])\n",
      "Epoch: 4192,Loss: 2.927664\n",
      "\tgrad: tensor([-0.0005,  0.0024])\n",
      "\tparams: tensor([  5.3652, -17.2907])\n",
      "Epoch: 4193,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3652, -17.2907])\n",
      "Epoch: 4194,Loss: 2.927663\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3652, -17.2907])\n",
      "Epoch: 4195,Loss: 2.927663\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3652, -17.2908])\n",
      "Epoch: 4196,Loss: 2.927665\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3652, -17.2908])\n",
      "Epoch: 4197,Loss: 2.927664\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3653, -17.2908])\n",
      "Epoch: 4198,Loss: 2.927663\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3653, -17.2908])\n",
      "Epoch: 4199,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3653, -17.2909])\n",
      "Epoch: 4200,Loss: 2.927664\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3653, -17.2909])\n",
      "Epoch: 4201,Loss: 2.927663\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3653, -17.2909])\n",
      "Epoch: 4202,Loss: 2.927661\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3653, -17.2909])\n",
      "Epoch: 4203,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3653, -17.2910])\n",
      "Epoch: 4204,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0024])\n",
      "\tparams: tensor([  5.3653, -17.2910])\n",
      "Epoch: 4205,Loss: 2.927663\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3653, -17.2910])\n",
      "Epoch: 4206,Loss: 2.927663\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3653, -17.2910])\n",
      "Epoch: 4207,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3653, -17.2910])\n",
      "Epoch: 4208,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3653, -17.2911])\n",
      "Epoch: 4209,Loss: 2.927663\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3653, -17.2911])\n",
      "Epoch: 4210,Loss: 2.927664\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3653, -17.2911])\n",
      "Epoch: 4211,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3653, -17.2911])\n",
      "Epoch: 4212,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3653, -17.2912])\n",
      "Epoch: 4213,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3653, -17.2912])\n",
      "Epoch: 4214,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3653, -17.2912])\n",
      "Epoch: 4215,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3653, -17.2912])\n",
      "Epoch: 4216,Loss: 2.927661\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3653, -17.2913])\n",
      "Epoch: 4217,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3653, -17.2913])\n",
      "Epoch: 4218,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3653, -17.2913])\n",
      "Epoch: 4219,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3653, -17.2913])\n",
      "Epoch: 4220,Loss: 2.927663\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3653, -17.2913])\n",
      "Epoch: 4221,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3653, -17.2914])\n",
      "Epoch: 4222,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3654, -17.2914])\n",
      "Epoch: 4223,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3654, -17.2914])\n",
      "Epoch: 4224,Loss: 2.927663\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3654, -17.2914])\n",
      "Epoch: 4225,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3654, -17.2915])\n",
      "Epoch: 4226,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3654, -17.2915])\n",
      "Epoch: 4227,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3654, -17.2915])\n",
      "Epoch: 4228,Loss: 2.927661\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3654, -17.2915])\n",
      "Epoch: 4229,Loss: 2.927661\n",
      "\tgrad: tensor([-0.0004,  0.0023])\n",
      "\tparams: tensor([  5.3654, -17.2915])\n",
      "Epoch: 4230,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3654, -17.2916])\n",
      "Epoch: 4231,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3654, -17.2916])\n",
      "Epoch: 4232,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3654, -17.2916])\n",
      "Epoch: 4233,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3654, -17.2916])\n",
      "Epoch: 4234,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3654, -17.2917])\n",
      "Epoch: 4235,Loss: 2.927661\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3654, -17.2917])\n",
      "Epoch: 4236,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3654, -17.2917])\n",
      "Epoch: 4237,Loss: 2.927661\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3654, -17.2917])\n",
      "Epoch: 4238,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3654, -17.2918])\n",
      "Epoch: 4239,Loss: 2.927661\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3654, -17.2918])\n",
      "Epoch: 4240,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3654, -17.2918])\n",
      "Epoch: 4241,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3654, -17.2918])\n",
      "Epoch: 4242,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3654, -17.2918])\n",
      "Epoch: 4243,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3654, -17.2919])\n",
      "Epoch: 4244,Loss: 2.927661\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3654, -17.2919])\n",
      "Epoch: 4245,Loss: 2.927661\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3654, -17.2919])\n",
      "Epoch: 4246,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3654, -17.2919])\n",
      "Epoch: 4247,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3655, -17.2920])\n",
      "Epoch: 4248,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3655, -17.2920])\n",
      "Epoch: 4249,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3655, -17.2920])\n",
      "Epoch: 4250,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3655, -17.2920])\n",
      "Epoch: 4251,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3655, -17.2920])\n",
      "Epoch: 4252,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3655, -17.2921])\n",
      "Epoch: 4253,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3655, -17.2921])\n",
      "Epoch: 4254,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3655, -17.2921])\n",
      "Epoch: 4255,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3655, -17.2921])\n",
      "Epoch: 4256,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3655, -17.2921])\n",
      "Epoch: 4257,Loss: 2.927661\n",
      "\tgrad: tensor([-0.0004,  0.0022])\n",
      "\tparams: tensor([  5.3655, -17.2922])\n",
      "Epoch: 4258,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3655, -17.2922])\n",
      "Epoch: 4259,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3655, -17.2922])\n",
      "Epoch: 4260,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3655, -17.2922])\n",
      "Epoch: 4261,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3655, -17.2922])\n",
      "Epoch: 4262,Loss: 2.927662\n",
      "\tgrad: tensor([-0.0003,  0.0021])\n",
      "\tparams: tensor([  5.3655, -17.2923])\n",
      "Epoch: 4263,Loss: 2.927658\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3655, -17.2923])\n",
      "Epoch: 4264,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3655, -17.2923])\n",
      "Epoch: 4265,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3655, -17.2923])\n",
      "Epoch: 4266,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3655, -17.2924])\n",
      "Epoch: 4267,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3655, -17.2924])\n",
      "Epoch: 4268,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3655, -17.2924])\n",
      "Epoch: 4269,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3655, -17.2924])\n",
      "Epoch: 4270,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3655, -17.2924])\n",
      "Epoch: 4271,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3655, -17.2925])\n",
      "Epoch: 4272,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3655, -17.2925])\n",
      "Epoch: 4273,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3655, -17.2925])\n",
      "Epoch: 4274,Loss: 2.927658\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3656, -17.2925])\n",
      "Epoch: 4275,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3656, -17.2925])\n",
      "Epoch: 4276,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3656, -17.2926])\n",
      "Epoch: 4277,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3656, -17.2926])\n",
      "Epoch: 4278,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3656, -17.2926])\n",
      "Epoch: 4279,Loss: 2.927658\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3656, -17.2926])\n",
      "Epoch: 4280,Loss: 2.927658\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3656, -17.2926])\n",
      "Epoch: 4281,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3656, -17.2927])\n",
      "Epoch: 4282,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3656, -17.2927])\n",
      "Epoch: 4283,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3656, -17.2927])\n",
      "Epoch: 4284,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0021])\n",
      "\tparams: tensor([  5.3656, -17.2927])\n",
      "Epoch: 4285,Loss: 2.927658\n",
      "\tgrad: tensor([-0.0004,  0.0020])\n",
      "\tparams: tensor([  5.3656, -17.2927])\n",
      "Epoch: 4286,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0004,  0.0020])\n",
      "\tparams: tensor([  5.3656, -17.2928])\n",
      "Epoch: 4287,Loss: 2.927658\n",
      "\tgrad: tensor([-0.0004,  0.0020])\n",
      "\tparams: tensor([  5.3656, -17.2928])\n",
      "Epoch: 4288,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0004,  0.0020])\n",
      "\tparams: tensor([  5.3656, -17.2928])\n",
      "Epoch: 4289,Loss: 2.927658\n",
      "\tgrad: tensor([-0.0004,  0.0020])\n",
      "\tparams: tensor([  5.3656, -17.2928])\n",
      "Epoch: 4290,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0004,  0.0020])\n",
      "\tparams: tensor([  5.3656, -17.2929])\n",
      "Epoch: 4291,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0004,  0.0020])\n",
      "\tparams: tensor([  5.3656, -17.2929])\n",
      "Epoch: 4292,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0004,  0.0020])\n",
      "\tparams: tensor([  5.3656, -17.2929])\n",
      "Epoch: 4293,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0004,  0.0020])\n",
      "\tparams: tensor([  5.3656, -17.2929])\n",
      "Epoch: 4294,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0003,  0.0020])\n",
      "\tparams: tensor([  5.3656, -17.2929])\n",
      "Epoch: 4295,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0004,  0.0020])\n",
      "\tparams: tensor([  5.3656, -17.2930])\n",
      "Epoch: 4296,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0004,  0.0020])\n",
      "\tparams: tensor([  5.3656, -17.2930])\n",
      "Epoch: 4297,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0004,  0.0020])\n",
      "\tparams: tensor([  5.3656, -17.2930])\n",
      "Epoch: 4298,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0004,  0.0020])\n",
      "\tparams: tensor([  5.3656, -17.2930])\n",
      "Epoch: 4299,Loss: 2.927658\n",
      "\tgrad: tensor([-0.0004,  0.0020])\n",
      "\tparams: tensor([  5.3656, -17.2930])\n",
      "Epoch: 4300,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0004,  0.0020])\n",
      "\tparams: tensor([  5.3656, -17.2931])\n",
      "Epoch: 4301,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0004,  0.0020])\n",
      "\tparams: tensor([  5.3657, -17.2931])\n",
      "Epoch: 4302,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0020])\n",
      "\tparams: tensor([  5.3657, -17.2931])\n",
      "Epoch: 4303,Loss: 2.927658\n",
      "\tgrad: tensor([-0.0003,  0.0020])\n",
      "\tparams: tensor([  5.3657, -17.2931])\n",
      "Epoch: 4304,Loss: 2.927658\n",
      "\tgrad: tensor([-0.0003,  0.0020])\n",
      "\tparams: tensor([  5.3657, -17.2931])\n",
      "Epoch: 4305,Loss: 2.927658\n",
      "\tgrad: tensor([-0.0003,  0.0020])\n",
      "\tparams: tensor([  5.3657, -17.2932])\n",
      "Epoch: 4306,Loss: 2.927658\n",
      "\tgrad: tensor([-0.0003,  0.0020])\n",
      "\tparams: tensor([  5.3657, -17.2932])\n",
      "Epoch: 4307,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0020])\n",
      "\tparams: tensor([  5.3657, -17.2932])\n",
      "Epoch: 4308,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0020])\n",
      "\tparams: tensor([  5.3657, -17.2932])\n",
      "Epoch: 4309,Loss: 2.927658\n",
      "\tgrad: tensor([-0.0003,  0.0020])\n",
      "\tparams: tensor([  5.3657, -17.2932])\n",
      "Epoch: 4310,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0020])\n",
      "\tparams: tensor([  5.3657, -17.2932])\n",
      "Epoch: 4311,Loss: 2.927660\n",
      "\tgrad: tensor([-0.0003,  0.0020])\n",
      "\tparams: tensor([  5.3657, -17.2933])\n",
      "Epoch: 4312,Loss: 2.927659\n",
      "\tgrad: tensor([-0.0003,  0.0020])\n",
      "\tparams: tensor([  5.3657, -17.2933])\n",
      "Epoch: 4313,Loss: 2.927658\n",
      "\tgrad: tensor([-0.0003,  0.0020])\n",
      "\tparams: tensor([  5.3657, -17.2933])\n",
      "Epoch: 4314,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3657, -17.2933])\n",
      "Epoch: 4315,Loss: 2.927658\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3657, -17.2933])\n",
      "Epoch: 4316,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3657, -17.2934])\n",
      "Epoch: 4317,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3657, -17.2934])\n",
      "Epoch: 4318,Loss: 2.927658\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3657, -17.2934])\n",
      "Epoch: 4319,Loss: 2.927658\n",
      "\tgrad: tensor([-0.0004,  0.0019])\n",
      "\tparams: tensor([  5.3657, -17.2934])\n",
      "Epoch: 4320,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0004,  0.0019])\n",
      "\tparams: tensor([  5.3657, -17.2934])\n",
      "Epoch: 4321,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0004,  0.0019])\n",
      "\tparams: tensor([  5.3657, -17.2935])\n",
      "Epoch: 4322,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3657, -17.2935])\n",
      "Epoch: 4323,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0004,  0.0019])\n",
      "\tparams: tensor([  5.3657, -17.2935])\n",
      "Epoch: 4324,Loss: 2.927658\n",
      "\tgrad: tensor([-0.0004,  0.0019])\n",
      "\tparams: tensor([  5.3657, -17.2935])\n",
      "Epoch: 4325,Loss: 2.927658\n",
      "\tgrad: tensor([-0.0004,  0.0019])\n",
      "\tparams: tensor([  5.3657, -17.2935])\n",
      "Epoch: 4326,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3657, -17.2936])\n",
      "Epoch: 4327,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3657, -17.2936])\n",
      "Epoch: 4328,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3657, -17.2936])\n",
      "Epoch: 4329,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3657, -17.2936])\n",
      "Epoch: 4330,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3657, -17.2936])\n",
      "Epoch: 4331,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3658, -17.2936])\n",
      "Epoch: 4332,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3658, -17.2937])\n",
      "Epoch: 4333,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3658, -17.2937])\n",
      "Epoch: 4334,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3658, -17.2937])\n",
      "Epoch: 4335,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3658, -17.2937])\n",
      "Epoch: 4336,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3658, -17.2937])\n",
      "Epoch: 4337,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3658, -17.2938])\n",
      "Epoch: 4338,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3658, -17.2938])\n",
      "Epoch: 4339,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3658, -17.2938])\n",
      "Epoch: 4340,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3658, -17.2938])\n",
      "Epoch: 4341,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0019])\n",
      "\tparams: tensor([  5.3658, -17.2938])\n",
      "Epoch: 4342,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0004,  0.0019])\n",
      "\tparams: tensor([  5.3658, -17.2939])\n",
      "Epoch: 4343,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0004,  0.0019])\n",
      "\tparams: tensor([  5.3658, -17.2939])\n",
      "Epoch: 4344,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0004,  0.0018])\n",
      "\tparams: tensor([  5.3658, -17.2939])\n",
      "Epoch: 4345,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0004,  0.0018])\n",
      "\tparams: tensor([  5.3658, -17.2939])\n",
      "Epoch: 4346,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0004,  0.0018])\n",
      "\tparams: tensor([  5.3658, -17.2939])\n",
      "Epoch: 4347,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3658, -17.2940])\n",
      "Epoch: 4348,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3658, -17.2940])\n",
      "Epoch: 4349,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3658, -17.2940])\n",
      "Epoch: 4350,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3658, -17.2940])\n",
      "Epoch: 4351,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3658, -17.2940])\n",
      "Epoch: 4352,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3658, -17.2941])\n",
      "Epoch: 4353,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3658, -17.2941])\n",
      "Epoch: 4354,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3658, -17.2941])\n",
      "Epoch: 4355,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3658, -17.2941])\n",
      "Epoch: 4356,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3658, -17.2941])\n",
      "Epoch: 4357,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3658, -17.2941])\n",
      "Epoch: 4358,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3658, -17.2942])\n",
      "Epoch: 4359,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3658, -17.2942])\n",
      "Epoch: 4360,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3658, -17.2942])\n",
      "Epoch: 4361,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3659, -17.2942])\n",
      "Epoch: 4362,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3659, -17.2942])\n",
      "Epoch: 4363,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3659, -17.2942])\n",
      "Epoch: 4364,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3659, -17.2943])\n",
      "Epoch: 4365,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3659, -17.2943])\n",
      "Epoch: 4366,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3659, -17.2943])\n",
      "Epoch: 4367,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3659, -17.2943])\n",
      "Epoch: 4368,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3659, -17.2943])\n",
      "Epoch: 4369,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3659, -17.2943])\n",
      "Epoch: 4370,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3659, -17.2944])\n",
      "Epoch: 4371,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3659, -17.2944])\n",
      "Epoch: 4372,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3659, -17.2944])\n",
      "Epoch: 4373,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3659, -17.2944])\n",
      "Epoch: 4374,Loss: 2.927657\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3659, -17.2944])\n",
      "Epoch: 4375,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3659, -17.2945])\n",
      "Epoch: 4376,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3659, -17.2945])\n",
      "Epoch: 4377,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3659, -17.2945])\n",
      "Epoch: 4378,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0018])\n",
      "\tparams: tensor([  5.3659, -17.2945])\n",
      "Epoch: 4379,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3659, -17.2945])\n",
      "Epoch: 4380,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3659, -17.2945])\n",
      "Epoch: 4381,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3659, -17.2946])\n",
      "Epoch: 4382,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3659, -17.2946])\n",
      "Epoch: 4383,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3659, -17.2946])\n",
      "Epoch: 4384,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3659, -17.2946])\n",
      "Epoch: 4385,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3659, -17.2946])\n",
      "Epoch: 4386,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3659, -17.2946])\n",
      "Epoch: 4387,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3659, -17.2947])\n",
      "Epoch: 4388,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3659, -17.2947])\n",
      "Epoch: 4389,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3659, -17.2947])\n",
      "Epoch: 4390,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3659, -17.2947])\n",
      "Epoch: 4391,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3659, -17.2947])\n",
      "Epoch: 4392,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3659, -17.2947])\n",
      "Epoch: 4393,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3659, -17.2948])\n",
      "Epoch: 4394,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3660, -17.2948])\n",
      "Epoch: 4395,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3660, -17.2948])\n",
      "Epoch: 4396,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3660, -17.2948])\n",
      "Epoch: 4397,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3660, -17.2948])\n",
      "Epoch: 4398,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3660, -17.2948])\n",
      "Epoch: 4399,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3660, -17.2949])\n",
      "Epoch: 4400,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3660, -17.2949])\n",
      "Epoch: 4401,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3660, -17.2949])\n",
      "Epoch: 4402,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3660, -17.2949])\n",
      "Epoch: 4403,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3660, -17.2949])\n",
      "Epoch: 4404,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3660, -17.2949])\n",
      "Epoch: 4405,Loss: 2.927656\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3660, -17.2950])\n",
      "Epoch: 4406,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3660, -17.2950])\n",
      "Epoch: 4407,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3660, -17.2950])\n",
      "Epoch: 4408,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3660, -17.2950])\n",
      "Epoch: 4409,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3660, -17.2950])\n",
      "Epoch: 4410,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3660, -17.2951])\n",
      "Epoch: 4411,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0017])\n",
      "\tparams: tensor([  5.3660, -17.2951])\n",
      "Epoch: 4412,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3660, -17.2951])\n",
      "Epoch: 4413,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3660, -17.2951])\n",
      "Epoch: 4414,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3660, -17.2951])\n",
      "Epoch: 4415,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3660, -17.2951])\n",
      "Epoch: 4416,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3660, -17.2952])\n",
      "Epoch: 4417,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3660, -17.2952])\n",
      "Epoch: 4418,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3660, -17.2952])\n",
      "Epoch: 4419,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3660, -17.2952])\n",
      "Epoch: 4420,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3660, -17.2952])\n",
      "Epoch: 4421,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3660, -17.2952])\n",
      "Epoch: 4422,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3660, -17.2953])\n",
      "Epoch: 4423,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3660, -17.2953])\n",
      "Epoch: 4424,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3660, -17.2953])\n",
      "Epoch: 4425,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3660, -17.2953])\n",
      "Epoch: 4426,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3660, -17.2953])\n",
      "Epoch: 4427,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3660, -17.2953])\n",
      "Epoch: 4428,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2953])\n",
      "Epoch: 4429,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2954])\n",
      "Epoch: 4430,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2954])\n",
      "Epoch: 4431,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2954])\n",
      "Epoch: 4432,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2954])\n",
      "Epoch: 4433,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2954])\n",
      "Epoch: 4434,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2954])\n",
      "Epoch: 4435,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2955])\n",
      "Epoch: 4436,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2955])\n",
      "Epoch: 4437,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2955])\n",
      "Epoch: 4438,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2955])\n",
      "Epoch: 4439,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2955])\n",
      "Epoch: 4440,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2955])\n",
      "Epoch: 4441,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2955])\n",
      "Epoch: 4442,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2956])\n",
      "Epoch: 4443,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0002,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2956])\n",
      "Epoch: 4444,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2956])\n",
      "Epoch: 4445,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2956])\n",
      "Epoch: 4446,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2956])\n",
      "Epoch: 4447,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2956])\n",
      "Epoch: 4448,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2957])\n",
      "Epoch: 4449,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0016])\n",
      "\tparams: tensor([  5.3661, -17.2957])\n",
      "Epoch: 4450,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3661, -17.2957])\n",
      "Epoch: 4451,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3661, -17.2957])\n",
      "Epoch: 4452,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3661, -17.2957])\n",
      "Epoch: 4453,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3661, -17.2957])\n",
      "Epoch: 4454,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3661, -17.2957])\n",
      "Epoch: 4455,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3661, -17.2958])\n",
      "Epoch: 4456,Loss: 2.927655\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3661, -17.2958])\n",
      "Epoch: 4457,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3661, -17.2958])\n",
      "Epoch: 4458,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3661, -17.2958])\n",
      "Epoch: 4459,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3661, -17.2958])\n",
      "Epoch: 4460,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3661, -17.2958])\n",
      "Epoch: 4461,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3661, -17.2959])\n",
      "Epoch: 4462,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3661, -17.2959])\n",
      "Epoch: 4463,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3661, -17.2959])\n",
      "Epoch: 4464,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3661, -17.2959])\n",
      "Epoch: 4465,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2959])\n",
      "Epoch: 4466,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2959])\n",
      "Epoch: 4467,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2959])\n",
      "Epoch: 4468,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2960])\n",
      "Epoch: 4469,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2960])\n",
      "Epoch: 4470,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2960])\n",
      "Epoch: 4471,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2960])\n",
      "Epoch: 4472,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2960])\n",
      "Epoch: 4473,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2960])\n",
      "Epoch: 4474,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2960])\n",
      "Epoch: 4475,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2961])\n",
      "Epoch: 4476,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2961])\n",
      "Epoch: 4477,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2961])\n",
      "Epoch: 4478,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2961])\n",
      "Epoch: 4479,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2961])\n",
      "Epoch: 4480,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2961])\n",
      "Epoch: 4481,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2962])\n",
      "Epoch: 4482,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2962])\n",
      "Epoch: 4483,Loss: 2.927654\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2962])\n",
      "Epoch: 4484,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2962])\n",
      "Epoch: 4485,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2962])\n",
      "Epoch: 4486,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2962])\n",
      "Epoch: 4487,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0015])\n",
      "\tparams: tensor([  5.3662, -17.2962])\n",
      "Epoch: 4488,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0003,  0.0014])\n",
      "\tparams: tensor([  5.3662, -17.2963])\n",
      "Epoch: 4489,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0014])\n",
      "\tparams: tensor([  5.3662, -17.2963])\n",
      "Epoch: 4490,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0003,  0.0014])\n",
      "\tparams: tensor([  5.3662, -17.2963])\n",
      "Epoch: 4491,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0003,  0.0014])\n",
      "\tparams: tensor([  5.3662, -17.2963])\n",
      "Epoch: 4492,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0003,  0.0014])\n",
      "\tparams: tensor([  5.3662, -17.2963])\n",
      "Epoch: 4493,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0014])\n",
      "\tparams: tensor([  5.3662, -17.2963])\n",
      "Epoch: 4494,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0014])\n",
      "\tparams: tensor([  5.3662, -17.2964])\n",
      "Epoch: 4495,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0003,  0.0014])\n",
      "\tparams: tensor([  5.3662, -17.2964])\n",
      "Epoch: 4496,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0003,  0.0014])\n",
      "\tparams: tensor([  5.3662, -17.2964])\n",
      "Epoch: 4497,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3662, -17.2964])\n",
      "Epoch: 4498,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3662, -17.2964])\n",
      "Epoch: 4499,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3662, -17.2964])\n",
      "Epoch: 4500,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3662, -17.2964])\n",
      "Epoch: 4501,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3662, -17.2964])\n",
      "Epoch: 4502,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3662, -17.2965])\n",
      "Epoch: 4503,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2965])\n",
      "Epoch: 4504,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2965])\n",
      "Epoch: 4505,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2965])\n",
      "Epoch: 4506,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2965])\n",
      "Epoch: 4507,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2965])\n",
      "Epoch: 4508,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2965])\n",
      "Epoch: 4509,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2966])\n",
      "Epoch: 4510,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2966])\n",
      "Epoch: 4511,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2966])\n",
      "Epoch: 4512,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2966])\n",
      "Epoch: 4513,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2966])\n",
      "Epoch: 4514,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2966])\n",
      "Epoch: 4515,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2966])\n",
      "Epoch: 4516,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2966])\n",
      "Epoch: 4517,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2967])\n",
      "Epoch: 4518,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2967])\n",
      "Epoch: 4519,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2967])\n",
      "Epoch: 4520,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2967])\n",
      "Epoch: 4521,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2967])\n",
      "Epoch: 4522,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2967])\n",
      "Epoch: 4523,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2967])\n",
      "Epoch: 4524,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2968])\n",
      "Epoch: 4525,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2968])\n",
      "Epoch: 4526,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2968])\n",
      "Epoch: 4527,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2968])\n",
      "Epoch: 4528,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2968])\n",
      "Epoch: 4529,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2968])\n",
      "Epoch: 4530,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2968])\n",
      "Epoch: 4531,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0014])\n",
      "\tparams: tensor([  5.3663, -17.2969])\n",
      "Epoch: 4532,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3663, -17.2969])\n",
      "Epoch: 4533,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3663, -17.2969])\n",
      "Epoch: 4534,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3663, -17.2969])\n",
      "Epoch: 4535,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3663, -17.2969])\n",
      "Epoch: 4536,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3663, -17.2969])\n",
      "Epoch: 4537,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3663, -17.2969])\n",
      "Epoch: 4538,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3663, -17.2969])\n",
      "Epoch: 4539,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3663, -17.2970])\n",
      "Epoch: 4540,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3663, -17.2970])\n",
      "Epoch: 4541,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3663, -17.2970])\n",
      "Epoch: 4542,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3663, -17.2970])\n",
      "Epoch: 4543,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3663, -17.2970])\n",
      "Epoch: 4544,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3663, -17.2970])\n",
      "Epoch: 4545,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2970])\n",
      "Epoch: 4546,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2971])\n",
      "Epoch: 4547,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2971])\n",
      "Epoch: 4548,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2971])\n",
      "Epoch: 4549,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2971])\n",
      "Epoch: 4550,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2971])\n",
      "Epoch: 4551,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2971])\n",
      "Epoch: 4552,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2971])\n",
      "Epoch: 4553,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2971])\n",
      "Epoch: 4554,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2972])\n",
      "Epoch: 4555,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2972])\n",
      "Epoch: 4556,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2972])\n",
      "Epoch: 4557,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2972])\n",
      "Epoch: 4558,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2972])\n",
      "Epoch: 4559,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2972])\n",
      "Epoch: 4560,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2972])\n",
      "Epoch: 4561,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2973])\n",
      "Epoch: 4562,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2973])\n",
      "Epoch: 4563,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2973])\n",
      "Epoch: 4564,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2973])\n",
      "Epoch: 4565,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2973])\n",
      "Epoch: 4566,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2973])\n",
      "Epoch: 4567,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2973])\n",
      "Epoch: 4568,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2973])\n",
      "Epoch: 4569,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2974])\n",
      "Epoch: 4570,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2974])\n",
      "Epoch: 4571,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2974])\n",
      "Epoch: 4572,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2974])\n",
      "Epoch: 4573,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0013])\n",
      "\tparams: tensor([  5.3664, -17.2974])\n",
      "Epoch: 4574,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3664, -17.2974])\n",
      "Epoch: 4575,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3664, -17.2974])\n",
      "Epoch: 4576,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3664, -17.2975])\n",
      "Epoch: 4577,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3664, -17.2975])\n",
      "Epoch: 4578,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3664, -17.2975])\n",
      "Epoch: 4579,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3664, -17.2975])\n",
      "Epoch: 4580,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3664, -17.2975])\n",
      "Epoch: 4581,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3664, -17.2975])\n",
      "Epoch: 4582,Loss: 2.927653\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3664, -17.2975])\n",
      "Epoch: 4583,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3664, -17.2975])\n",
      "Epoch: 4584,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3664, -17.2976])\n",
      "Epoch: 4585,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3664, -17.2976])\n",
      "Epoch: 4586,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3664, -17.2976])\n",
      "Epoch: 4587,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3664, -17.2976])\n",
      "Epoch: 4588,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3664, -17.2976])\n",
      "Epoch: 4589,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2976])\n",
      "Epoch: 4590,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2976])\n",
      "Epoch: 4591,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2976])\n",
      "Epoch: 4592,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2976])\n",
      "Epoch: 4593,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2977])\n",
      "Epoch: 4594,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2977])\n",
      "Epoch: 4595,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2977])\n",
      "Epoch: 4596,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2977])\n",
      "Epoch: 4597,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2977])\n",
      "Epoch: 4598,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2977])\n",
      "Epoch: 4599,Loss: 2.927652\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2977])\n",
      "Epoch: 4600,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2977])\n",
      "Epoch: 4601,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2977])\n",
      "Epoch: 4602,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2978])\n",
      "Epoch: 4603,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2978])\n",
      "Epoch: 4604,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2978])\n",
      "Epoch: 4605,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2978])\n",
      "Epoch: 4606,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2978])\n",
      "Epoch: 4607,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2978])\n",
      "Epoch: 4608,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2978])\n",
      "Epoch: 4609,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2978])\n",
      "Epoch: 4610,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2978])\n",
      "Epoch: 4611,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2979])\n",
      "Epoch: 4612,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2979])\n",
      "Epoch: 4613,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2979])\n",
      "Epoch: 4614,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2979])\n",
      "Epoch: 4615,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2979])\n",
      "Epoch: 4616,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2979])\n",
      "Epoch: 4617,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2979])\n",
      "Epoch: 4618,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2979])\n",
      "Epoch: 4619,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2980])\n",
      "Epoch: 4620,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2980])\n",
      "Epoch: 4621,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2980])\n",
      "Epoch: 4622,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2980])\n",
      "Epoch: 4623,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2980])\n",
      "Epoch: 4624,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2980])\n",
      "Epoch: 4625,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2980])\n",
      "Epoch: 4626,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0012])\n",
      "\tparams: tensor([  5.3665, -17.2980])\n",
      "Epoch: 4627,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3665, -17.2980])\n",
      "Epoch: 4628,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3665, -17.2981])\n",
      "Epoch: 4629,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3665, -17.2981])\n",
      "Epoch: 4630,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3665, -17.2981])\n",
      "Epoch: 4631,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3665, -17.2981])\n",
      "Epoch: 4632,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3665, -17.2981])\n",
      "Epoch: 4633,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3665, -17.2981])\n",
      "Epoch: 4634,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3665, -17.2981])\n",
      "Epoch: 4635,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3665, -17.2981])\n",
      "Epoch: 4636,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3665, -17.2981])\n",
      "Epoch: 4637,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3665, -17.2982])\n",
      "Epoch: 4638,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3665, -17.2982])\n",
      "Epoch: 4639,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2982])\n",
      "Epoch: 4640,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2982])\n",
      "Epoch: 4641,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2982])\n",
      "Epoch: 4642,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2982])\n",
      "Epoch: 4643,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2982])\n",
      "Epoch: 4644,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2982])\n",
      "Epoch: 4645,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2982])\n",
      "Epoch: 4646,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2983])\n",
      "Epoch: 4647,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2983])\n",
      "Epoch: 4648,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2983])\n",
      "Epoch: 4649,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2983])\n",
      "Epoch: 4650,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2983])\n",
      "Epoch: 4651,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2983])\n",
      "Epoch: 4652,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2983])\n",
      "Epoch: 4653,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2983])\n",
      "Epoch: 4654,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2984])\n",
      "Epoch: 4655,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2984])\n",
      "Epoch: 4656,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2984])\n",
      "Epoch: 4657,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2984])\n",
      "Epoch: 4658,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2984])\n",
      "Epoch: 4659,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2984])\n",
      "Epoch: 4660,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2984])\n",
      "Epoch: 4661,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2984])\n",
      "Epoch: 4662,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2984])\n",
      "Epoch: 4663,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2985])\n",
      "Epoch: 4664,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2985])\n",
      "Epoch: 4665,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2985])\n",
      "Epoch: 4666,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2985])\n",
      "Epoch: 4667,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2985])\n",
      "Epoch: 4668,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2985])\n",
      "Epoch: 4669,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2985])\n",
      "Epoch: 4670,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2985])\n",
      "Epoch: 4671,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2985])\n",
      "Epoch: 4672,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2986])\n",
      "Epoch: 4673,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2986])\n",
      "Epoch: 4674,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2986])\n",
      "Epoch: 4675,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0011])\n",
      "\tparams: tensor([  5.3666, -17.2986])\n",
      "Epoch: 4676,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3666, -17.2986])\n",
      "Epoch: 4677,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3666, -17.2986])\n",
      "Epoch: 4678,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3666, -17.2986])\n",
      "Epoch: 4679,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3666, -17.2986])\n",
      "Epoch: 4680,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3666, -17.2986])\n",
      "Epoch: 4681,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3666, -17.2987])\n",
      "Epoch: 4682,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3666, -17.2987])\n",
      "Epoch: 4683,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3666, -17.2987])\n",
      "Epoch: 4684,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3666, -17.2987])\n",
      "Epoch: 4685,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3666, -17.2987])\n",
      "Epoch: 4686,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3666, -17.2987])\n",
      "Epoch: 4687,Loss: 2.927651\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3666, -17.2987])\n",
      "Epoch: 4688,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3666, -17.2987])\n",
      "Epoch: 4689,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3666, -17.2987])\n",
      "Epoch: 4690,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2987])\n",
      "Epoch: 4691,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2987])\n",
      "Epoch: 4692,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2988])\n",
      "Epoch: 4693,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2988])\n",
      "Epoch: 4694,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2988])\n",
      "Epoch: 4695,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2988])\n",
      "Epoch: 4696,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2988])\n",
      "Epoch: 4697,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2988])\n",
      "Epoch: 4698,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2988])\n",
      "Epoch: 4699,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2988])\n",
      "Epoch: 4700,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2988])\n",
      "Epoch: 4701,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2988])\n",
      "Epoch: 4702,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2989])\n",
      "Epoch: 4703,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2989])\n",
      "Epoch: 4704,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2989])\n",
      "Epoch: 4705,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2989])\n",
      "Epoch: 4706,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2989])\n",
      "Epoch: 4707,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2989])\n",
      "Epoch: 4708,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2989])\n",
      "Epoch: 4709,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2989])\n",
      "Epoch: 4710,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2989])\n",
      "Epoch: 4711,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2989])\n",
      "Epoch: 4712,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2989])\n",
      "Epoch: 4713,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2990])\n",
      "Epoch: 4714,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2990])\n",
      "Epoch: 4715,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2990])\n",
      "Epoch: 4716,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2990])\n",
      "Epoch: 4717,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2990])\n",
      "Epoch: 4718,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2990])\n",
      "Epoch: 4719,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2990])\n",
      "Epoch: 4720,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2990])\n",
      "Epoch: 4721,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2990])\n",
      "Epoch: 4722,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2990])\n",
      "Epoch: 4723,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2991])\n",
      "Epoch: 4724,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2991])\n",
      "Epoch: 4725,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2991])\n",
      "Epoch: 4726,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2991])\n",
      "Epoch: 4727,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2991])\n",
      "Epoch: 4728,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2991])\n",
      "Epoch: 4729,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2991])\n",
      "Epoch: 4730,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2991])\n",
      "Epoch: 4731,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2991])\n",
      "Epoch: 4732,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2991])\n",
      "Epoch: 4733,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2991])\n",
      "Epoch: 4734,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2992])\n",
      "Epoch: 4735,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2992])\n",
      "Epoch: 4736,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2992])\n",
      "Epoch: 4737,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2992])\n",
      "Epoch: 4738,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0010])\n",
      "\tparams: tensor([  5.3667, -17.2992])\n",
      "Epoch: 4739,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3667, -17.2992])\n",
      "Epoch: 4740,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3667, -17.2992])\n",
      "Epoch: 4741,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3667, -17.2992])\n",
      "Epoch: 4742,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3667, -17.2992])\n",
      "Epoch: 4743,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3667, -17.2992])\n",
      "Epoch: 4744,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3667, -17.2993])\n",
      "Epoch: 4745,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3667, -17.2993])\n",
      "Epoch: 4746,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3667, -17.2993])\n",
      "Epoch: 4747,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3667, -17.2993])\n",
      "Epoch: 4748,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3667, -17.2993])\n",
      "Epoch: 4749,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3667, -17.2993])\n",
      "Epoch: 4750,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2993])\n",
      "Epoch: 4751,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2993])\n",
      "Epoch: 4752,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2993])\n",
      "Epoch: 4753,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2993])\n",
      "Epoch: 4754,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2993])\n",
      "Epoch: 4755,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2994])\n",
      "Epoch: 4756,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2994])\n",
      "Epoch: 4757,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2994])\n",
      "Epoch: 4758,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2994])\n",
      "Epoch: 4759,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2994])\n",
      "Epoch: 4760,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2994])\n",
      "Epoch: 4761,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2994])\n",
      "Epoch: 4762,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2994])\n",
      "Epoch: 4763,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2994])\n",
      "Epoch: 4764,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2994])\n",
      "Epoch: 4765,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2995])\n",
      "Epoch: 4766,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2995])\n",
      "Epoch: 4767,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2995])\n",
      "Epoch: 4768,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2995])\n",
      "Epoch: 4769,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2995])\n",
      "Epoch: 4770,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2995])\n",
      "Epoch: 4771,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2995])\n",
      "Epoch: 4772,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2995])\n",
      "Epoch: 4773,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2995])\n",
      "Epoch: 4774,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2995])\n",
      "Epoch: 4775,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2995])\n",
      "Epoch: 4776,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2996])\n",
      "Epoch: 4777,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2996])\n",
      "Epoch: 4778,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2996])\n",
      "Epoch: 4779,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2996])\n",
      "Epoch: 4780,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2996])\n",
      "Epoch: 4781,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2996])\n",
      "Epoch: 4782,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2996])\n",
      "Epoch: 4783,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2996])\n",
      "Epoch: 4784,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2996])\n",
      "Epoch: 4785,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2996])\n",
      "Epoch: 4786,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2997])\n",
      "Epoch: 4787,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2997])\n",
      "Epoch: 4788,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2997])\n",
      "Epoch: 4789,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2997])\n",
      "Epoch: 4790,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2997])\n",
      "Epoch: 4791,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2997])\n",
      "Epoch: 4792,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2997])\n",
      "Epoch: 4793,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2997])\n",
      "Epoch: 4794,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2997])\n",
      "Epoch: 4795,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2997])\n",
      "Epoch: 4796,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2997])\n",
      "Epoch: 4797,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0002,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2997])\n",
      "Epoch: 4798,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2998])\n",
      "Epoch: 4799,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2998])\n",
      "Epoch: 4800,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2998])\n",
      "Epoch: 4801,Loss: 2.927646\n",
      "\tgrad: tensor([-0.0001,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2998])\n",
      "Epoch: 4802,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2998])\n",
      "Epoch: 4803,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0009])\n",
      "\tparams: tensor([  5.3668, -17.2998])\n",
      "Epoch: 4804,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3668, -17.2998])\n",
      "Epoch: 4805,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3668, -17.2998])\n",
      "Epoch: 4806,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3668, -17.2998])\n",
      "Epoch: 4807,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3668, -17.2998])\n",
      "Epoch: 4808,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3668, -17.2998])\n",
      "Epoch: 4809,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3668, -17.2998])\n",
      "Epoch: 4810,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3668, -17.2998])\n",
      "Epoch: 4811,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3668, -17.2999])\n",
      "Epoch: 4812,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3668, -17.2999])\n",
      "Epoch: 4813,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.2999])\n",
      "Epoch: 4814,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.2999])\n",
      "Epoch: 4815,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.2999])\n",
      "Epoch: 4816,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.2999])\n",
      "Epoch: 4817,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.2999])\n",
      "Epoch: 4818,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.2999])\n",
      "Epoch: 4819,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.2999])\n",
      "Epoch: 4820,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.2999])\n",
      "Epoch: 4821,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.2999])\n",
      "Epoch: 4822,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.2999])\n",
      "Epoch: 4823,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.2999])\n",
      "Epoch: 4824,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3000])\n",
      "Epoch: 4825,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3000])\n",
      "Epoch: 4826,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3000])\n",
      "Epoch: 4827,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3000])\n",
      "Epoch: 4828,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3000])\n",
      "Epoch: 4829,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3000])\n",
      "Epoch: 4830,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3000])\n",
      "Epoch: 4831,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3000])\n",
      "Epoch: 4832,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3000])\n",
      "Epoch: 4833,Loss: 2.927646\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3000])\n",
      "Epoch: 4834,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3000])\n",
      "Epoch: 4835,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3000])\n",
      "Epoch: 4836,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3000])\n",
      "Epoch: 4837,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3001])\n",
      "Epoch: 4838,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3001])\n",
      "Epoch: 4839,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3001])\n",
      "Epoch: 4840,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3001])\n",
      "Epoch: 4841,Loss: 2.927650\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3001])\n",
      "Epoch: 4842,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3001])\n",
      "Epoch: 4843,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3001])\n",
      "Epoch: 4844,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3001])\n",
      "Epoch: 4845,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3001])\n",
      "Epoch: 4846,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3001])\n",
      "Epoch: 4847,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3001])\n",
      "Epoch: 4848,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3001])\n",
      "Epoch: 4849,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3001])\n",
      "Epoch: 4850,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3002])\n",
      "Epoch: 4851,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3002])\n",
      "Epoch: 4852,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3002])\n",
      "Epoch: 4853,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3002])\n",
      "Epoch: 4854,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3002])\n",
      "Epoch: 4855,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3002])\n",
      "Epoch: 4856,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3002])\n",
      "Epoch: 4857,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3002])\n",
      "Epoch: 4858,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3002])\n",
      "Epoch: 4859,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3002])\n",
      "Epoch: 4860,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3002])\n",
      "Epoch: 4861,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3002])\n",
      "Epoch: 4862,Loss: 2.927645\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3002])\n",
      "Epoch: 4863,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3003])\n",
      "Epoch: 4864,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3003])\n",
      "Epoch: 4865,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3003])\n",
      "Epoch: 4866,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3003])\n",
      "Epoch: 4867,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3003])\n",
      "Epoch: 4868,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3003])\n",
      "Epoch: 4869,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3003])\n",
      "Epoch: 4870,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3003])\n",
      "Epoch: 4871,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3003])\n",
      "Epoch: 4872,Loss: 2.927646\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3003])\n",
      "Epoch: 4873,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3003])\n",
      "Epoch: 4874,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3003])\n",
      "Epoch: 4875,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3003])\n",
      "Epoch: 4876,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3004])\n",
      "Epoch: 4877,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3004])\n",
      "Epoch: 4878,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3004])\n",
      "Epoch: 4879,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3004])\n",
      "Epoch: 4880,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3004])\n",
      "Epoch: 4881,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0008])\n",
      "\tparams: tensor([  5.3669, -17.3004])\n",
      "Epoch: 4882,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3669, -17.3004])\n",
      "Epoch: 4883,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3669, -17.3004])\n",
      "Epoch: 4884,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3669, -17.3004])\n",
      "Epoch: 4885,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3669, -17.3004])\n",
      "Epoch: 4886,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3669, -17.3004])\n",
      "Epoch: 4887,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3004])\n",
      "Epoch: 4888,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3004])\n",
      "Epoch: 4889,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3005])\n",
      "Epoch: 4890,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3005])\n",
      "Epoch: 4891,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3005])\n",
      "Epoch: 4892,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3005])\n",
      "Epoch: 4893,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3005])\n",
      "Epoch: 4894,Loss: 2.927646\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3005])\n",
      "Epoch: 4895,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3005])\n",
      "Epoch: 4896,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3005])\n",
      "Epoch: 4897,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3005])\n",
      "Epoch: 4898,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3005])\n",
      "Epoch: 4899,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3005])\n",
      "Epoch: 4900,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3005])\n",
      "Epoch: 4901,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3005])\n",
      "Epoch: 4902,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3006])\n",
      "Epoch: 4903,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3006])\n",
      "Epoch: 4904,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3006])\n",
      "Epoch: 4905,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3006])\n",
      "Epoch: 4906,Loss: 2.927646\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3006])\n",
      "Epoch: 4907,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3006])\n",
      "Epoch: 4908,Loss: 2.927646\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3006])\n",
      "Epoch: 4909,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3006])\n",
      "Epoch: 4910,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3006])\n",
      "Epoch: 4911,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3006])\n",
      "Epoch: 4912,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3006])\n",
      "Epoch: 4913,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3006])\n",
      "Epoch: 4914,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3006])\n",
      "Epoch: 4915,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3006])\n",
      "Epoch: 4916,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3007])\n",
      "Epoch: 4917,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3007])\n",
      "Epoch: 4918,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3007])\n",
      "Epoch: 4919,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3007])\n",
      "Epoch: 4920,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3007])\n",
      "Epoch: 4921,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3007])\n",
      "Epoch: 4922,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3007])\n",
      "Epoch: 4923,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3007])\n",
      "Epoch: 4924,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3007])\n",
      "Epoch: 4925,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3007])\n",
      "Epoch: 4926,Loss: 2.927646\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3007])\n",
      "Epoch: 4927,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3007])\n",
      "Epoch: 4928,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3007])\n",
      "Epoch: 4929,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3008])\n",
      "Epoch: 4930,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3008])\n",
      "Epoch: 4931,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3008])\n",
      "Epoch: 4932,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3008])\n",
      "Epoch: 4933,Loss: 2.927646\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3008])\n",
      "Epoch: 4934,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3008])\n",
      "Epoch: 4935,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3008])\n",
      "Epoch: 4936,Loss: 2.927646\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3008])\n",
      "Epoch: 4937,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3008])\n",
      "Epoch: 4938,Loss: 2.927646\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3008])\n",
      "Epoch: 4939,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3008])\n",
      "Epoch: 4940,Loss: 2.927646\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3008])\n",
      "Epoch: 4941,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3008])\n",
      "Epoch: 4942,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3009])\n",
      "Epoch: 4943,Loss: 2.927646\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3009])\n",
      "Epoch: 4944,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3009])\n",
      "Epoch: 4945,Loss: 2.927646\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3009])\n",
      "Epoch: 4946,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3009])\n",
      "Epoch: 4947,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3009])\n",
      "Epoch: 4948,Loss: 2.927649\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3009])\n",
      "Epoch: 4949,Loss: 2.927646\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3009])\n",
      "Epoch: 4950,Loss: 2.927648\n",
      "\tgrad: tensor([-9.9361e-05,  6.6355e-04])\n",
      "\tparams: tensor([  5.3670, -17.3009])\n",
      "Epoch: 4951,Loss: 2.927646\n",
      "\tgrad: tensor([-9.5367e-05,  6.6292e-04])\n",
      "\tparams: tensor([  5.3670, -17.3009])\n",
      "Epoch: 4952,Loss: 2.927646\n",
      "\tgrad: tensor([-9.6858e-05,  6.6188e-04])\n",
      "\tparams: tensor([  5.3670, -17.3009])\n",
      "Epoch: 4953,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3009])\n",
      "Epoch: 4954,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3009])\n",
      "Epoch: 4955,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3009])\n",
      "Epoch: 4956,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3009])\n",
      "Epoch: 4957,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3009])\n",
      "Epoch: 4958,Loss: 2.927646\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3009])\n",
      "Epoch: 4959,Loss: 2.927648\n",
      "\tgrad: tensor([-9.8228e-05,  6.5479e-04])\n",
      "\tparams: tensor([  5.3670, -17.3010])\n",
      "Epoch: 4960,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3010])\n",
      "Epoch: 4961,Loss: 2.927648\n",
      "\tgrad: tensor([-9.8288e-05,  6.5270e-04])\n",
      "\tparams: tensor([  5.3670, -17.3010])\n",
      "Epoch: 4962,Loss: 2.927646\n",
      "\tgrad: tensor([-0.0001,  0.0007])\n",
      "\tparams: tensor([  5.3670, -17.3010])\n",
      "Epoch: 4963,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3670, -17.3010])\n",
      "Epoch: 4964,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3670, -17.3010])\n",
      "Epoch: 4965,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3670, -17.3010])\n",
      "Epoch: 4966,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3670, -17.3010])\n",
      "Epoch: 4967,Loss: 2.927646\n",
      "\tgrad: tensor([-9.7990e-05,  6.4683e-04])\n",
      "\tparams: tensor([  5.3671, -17.3010])\n",
      "Epoch: 4968,Loss: 2.927647\n",
      "\tgrad: tensor([-9.7573e-05,  6.4588e-04])\n",
      "\tparams: tensor([  5.3671, -17.3010])\n",
      "Epoch: 4969,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3010])\n",
      "Epoch: 4970,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3010])\n",
      "Epoch: 4971,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3010])\n",
      "Epoch: 4972,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3010])\n",
      "Epoch: 4973,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3010])\n",
      "Epoch: 4974,Loss: 2.927646\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3010])\n",
      "Epoch: 4975,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3010])\n",
      "Epoch: 4976,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3011])\n",
      "Epoch: 4977,Loss: 2.927647\n",
      "\tgrad: tensor([-9.5606e-05,  6.3694e-04])\n",
      "\tparams: tensor([  5.3671, -17.3011])\n",
      "Epoch: 4978,Loss: 2.927648\n",
      "\tgrad: tensor([-9.8169e-05,  6.3545e-04])\n",
      "\tparams: tensor([  5.3671, -17.3011])\n",
      "Epoch: 4979,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3011])\n",
      "Epoch: 4980,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3011])\n",
      "Epoch: 4981,Loss: 2.927646\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3011])\n",
      "Epoch: 4982,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3011])\n",
      "Epoch: 4983,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3011])\n",
      "Epoch: 4984,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3011])\n",
      "Epoch: 4985,Loss: 2.927646\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3011])\n",
      "Epoch: 4986,Loss: 2.927648\n",
      "\tgrad: tensor([-9.6440e-05,  6.2808e-04])\n",
      "\tparams: tensor([  5.3671, -17.3011])\n",
      "Epoch: 4987,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3011])\n",
      "Epoch: 4988,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3011])\n",
      "Epoch: 4989,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3011])\n",
      "Epoch: 4990,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3011])\n",
      "Epoch: 4991,Loss: 2.927646\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3011])\n",
      "Epoch: 4992,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3011])\n",
      "Epoch: 4993,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3011])\n",
      "Epoch: 4994,Loss: 2.927646\n",
      "\tgrad: tensor([-9.2626e-05,  6.2042e-04])\n",
      "\tparams: tensor([  5.3671, -17.3012])\n",
      "Epoch: 4995,Loss: 2.927647\n",
      "\tgrad: tensor([-9.8884e-05,  6.1837e-04])\n",
      "\tparams: tensor([  5.3671, -17.3012])\n",
      "Epoch: 4996,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3012])\n",
      "Epoch: 4997,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3012])\n",
      "Epoch: 4998,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3012])\n",
      "Epoch: 4999,Loss: 2.927647\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3012])\n",
      "Epoch: 5000,Loss: 2.927648\n",
      "\tgrad: tensor([-0.0001,  0.0006])\n",
      "\tparams: tensor([  5.3671, -17.3012])\n"
     ]
    },
    {
     "data": {
      "text/plain": "tensor([  5.3671, -17.3012])"
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 进行足够次数的迭代\n",
    "training_loop(n_epochs=5000,\n",
    "              learning_rate=1e-2,\n",
    "              params=torch.tensor([1.0,0.0]),\n",
    "              t_u=t_un,\n",
    "              t_c = t_c\n",
    "              )"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-12T02:50:03.241457Z",
     "start_time": "2023-10-12T02:49:58.649459400Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "t_p = model(t_un,5.3671,-17.3021)\n",
    "plt.xlabel('Temperature(F)')\n",
    "plt.ylabel('Temperature(C)')\n",
    "plt.plot(t_u.numpy(),t_p.detach().numpy())\n",
    "plt.plot(t_u.numpy(),t_c.numpy(),'o')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-12T02:57:10.987408300Z",
     "start_time": "2023-10-12T02:57:10.743420900Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "### PyTorch自动求导(反向传播)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "outputs": [
    {
     "data": {
      "text/plain": "True"
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def model(t_u,w,b):\n",
    "    return w*t_u+b\n",
    "\n",
    "def loss_fn(t_p,t_c):\n",
    "    squared_diffs = (t_p-t_c)**2\n",
    "    return squared_diffs.mean()\n",
    "\n",
    "params = torch.tensor([1.0,0.0],requires_grad=True) # 开启自动求导\n",
    "params.grad is None"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-12T03:11:03.714496900Z",
     "start_time": "2023-10-12T03:11:03.673506800Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "outputs": [
    {
     "data": {
      "text/plain": "tensor([4517.2969,   82.6000])"
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 通常,我们从一个requires_grad为True的张量开始,调用模型并计算损失函数,然后反向调用损失张量\n",
    "loss = loss_fn(model(t_u,*params),t_c)\n",
    "loss.backward() # 开始反向求导\n",
    "params.grad"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-12T03:13:54.384495800Z",
     "start_time": "2023-10-12T03:13:52.138363Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "outputs": [],
   "source": [
    "# 每次调用lossbackward()前需要将grad属性清零\n",
    "def training_loop(n_epochs,learning_rate,params,t_u,t_c):\n",
    "    for epoch in range(1,n_epochs+1):\n",
    "        if params.grad is not None:\n",
    "            params.grad.zero_()\n",
    "\n",
    "        t_p = model(t_u,*params)\n",
    "        loss = loss_fn(t_p,t_c)\n",
    "        loss.backward()\n",
    "\n",
    "        with torch.no_grad():\n",
    "            params-=learning_rate*params.grad\n",
    "\n",
    "        if epoch%500==0:\n",
    "            print('Epoch %d,Loss%f'%(epoch,float(loss)))\n",
    "\n",
    "\n",
    "    return params"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-12T03:23:26.880754100Z",
     "start_time": "2023-10-12T03:23:26.833754900Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 500,Loss7.860115\n",
      "Epoch 1000,Loss3.828538\n",
      "Epoch 1500,Loss3.092191\n",
      "Epoch 2000,Loss2.957698\n",
      "Epoch 2500,Loss2.933134\n",
      "Epoch 3000,Loss2.928648\n",
      "Epoch 3500,Loss2.927830\n",
      "Epoch 4000,Loss2.927679\n",
      "Epoch 4500,Loss2.927652\n",
      "Epoch 5000,Loss2.927647\n"
     ]
    },
    {
     "data": {
      "text/plain": "tensor([  5.3671, -17.3012], requires_grad=True)"
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "training_loop(\n",
    "    n_epochs=5000,\n",
    "    learning_rate=1e-2,\n",
    "    params=torch.tensor([1.0,0.0],requires_grad=True),\n",
    "    t_u=t_un,\n",
    "    t_c=t_c\n",
    ")"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-12T03:24:35.086153300Z",
     "start_time": "2023-10-12T03:24:33.116131200Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "### 5.5.2.优化器"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "outputs": [
    {
     "data": {
      "text/plain": "['ASGD',\n 'Adadelta',\n 'Adagrad',\n 'Adam',\n 'AdamW',\n 'Adamax',\n 'LBFGS',\n 'NAdam',\n 'Optimizer',\n 'RAdam',\n 'RMSprop',\n 'Rprop',\n 'SGD',\n 'SparseAdam',\n '__builtins__',\n '__cached__',\n '__doc__',\n '__file__',\n '__loader__',\n '__name__',\n '__package__',\n '__path__',\n '__spec__',\n '_functional',\n '_multi_tensor',\n 'lr_scheduler',\n 'swa_utils']"
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看下PyTorch的自带的优化器\n",
    "import torch.optim as optim\n",
    "dir(optim)\n",
    "# 每个优化器构造函数都接受一个参数列表(设置requires_grad=true)作为第一个输入，传递给优化器的所有参数都将保留在优化器对象中,以便更新并访问他们的grad属性"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-13T05:16:21.605091900Z",
     "start_time": "2023-10-13T05:15:54.819093500Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "outputs": [],
   "source": [
    "import torch\n",
    "t_c =[0.5,14.0,15.0,28.0,11.0,8.0,3.0,-4.0,6.0,13.0,21.0] # 旧温度计\n",
    "t_u =[35.7,55.9,58.2,81.9,56.3,48.9,33.9,21.8,48.4,60.4,68.4] # 新温度计\n",
    "\n",
    "t_c = torch.tensor(t_c)\n",
    "t_u = torch.tensor(t_u)\n",
    "\n",
    "## 选择线性模型做尝试\n",
    "def model(t_u,w,b):\n",
    "    return t_u*w +b\n",
    "\n",
    "## 损失函数\n",
    "def loss_fn(t_p,t_c):\n",
    "    '''\n",
    "    :param t_p: 预测值\n",
    "    :param t_c: 实际值\n",
    "    :return: 损失值\n",
    "    '''\n",
    "    squared_diffs = (t_p-t_c)**2\n",
    "    return squared_diffs.mean() # 返回损失值的平均数"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-13T05:22:39.927704900Z",
     "start_time": "2023-10-13T05:22:38.903704300Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [
    {
     "data": {
      "text/plain": "tensor([ 9.5483e-01, -8.2600e-04], requires_grad=True)"
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 使用一个梯度下降优化器\n",
    "params = torch.tensor([1.0,0.0],requires_grad=True)\n",
    "learning_rate = 1e-5\n",
    "optimizer = optim.SGD([params],lr=learning_rate)\n",
    "\n",
    "t_p = model(t_u,*params)\n",
    "loss = loss_fn(t_p,t_c)\n",
    "loss.backward()\n",
    "optimizer.step()\n",
    "params # params的值在调用step的时候更新"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-13T05:32:51.571279900Z",
     "start_time": "2023-10-13T05:32:46.110885100Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "outputs": [
    {
     "data": {
      "text/plain": "tensor([1.7761, 0.1064], requires_grad=True)"
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "params = torch.tensor([1.0,0.0],requires_grad=True)\n",
    "learning_rate = 1e-2\n",
    "optimizer = optim.SGD([params],lr=learning_rate)\n",
    "\n",
    "t_un = 0.1*t_u\n",
    "\n",
    "t_p = model(t_un,*params)\n",
    "loss = loss_fn(t_p,t_c)\n",
    "\n",
    "optimizer.zero_grad() # 梯度清0,在调用loss.backward()之前都需要清零。\n",
    "loss.backward()\n",
    "optimizer.step()\n",
    "\n",
    "params"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-13T05:45:52.361060Z",
     "start_time": "2023-10-13T05:45:52.346057300Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "outputs": [],
   "source": [
    "def training_loop(n_epochs,optimizer,params,t_u,t_c):\n",
    "    for epoch in range(1,n_epochs+1):\n",
    "        t_p = model(t_u,*params)\n",
    "        loss = loss_fn(t_p,t_c)\n",
    "\n",
    "\n",
    "        optimizer.zero_grad()\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "\n",
    "        if epoch%500 ==0:\n",
    "            print('Epoch:%d,Loss:%f'%(epoch,float(loss)))\n",
    "    return params"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-13T05:56:03.942688600Z",
     "start_time": "2023-10-13T05:56:03.910688400Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch:500,Loss:7.860115\n",
      "Epoch:1000,Loss:3.828538\n",
      "Epoch:1500,Loss:3.092191\n",
      "Epoch:2000,Loss:2.957698\n",
      "Epoch:2500,Loss:2.933134\n",
      "Epoch:3000,Loss:2.928648\n",
      "Epoch:3500,Loss:2.927830\n",
      "Epoch:4000,Loss:2.927679\n",
      "Epoch:4500,Loss:2.927652\n",
      "Epoch:5000,Loss:2.927647\n"
     ]
    },
    {
     "data": {
      "text/plain": "tensor([  5.3671, -17.3012], requires_grad=True)"
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "params = torch.tensor([1.0,0.0],requires_grad=True)\n",
    "learning_rate=1e-2\n",
    "optimizer = optim.SGD([params],lr=learning_rate)\n",
    "training_loop(n_epochs=5000,optimizer=optimizer,params=params,t_u=t_un,t_c=t_c)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-13T05:58:02.224323100Z",
     "start_time": "2023-10-13T05:58:00.363324800Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch:500,Loss:7.612900\n",
      "Epoch:1000,Loss:3.086700\n",
      "Epoch:1500,Loss:2.928579\n",
      "Epoch:2000,Loss:2.927644\n"
     ]
    },
    {
     "data": {
      "text/plain": "tensor([  0.5367, -17.3021], requires_grad=True)"
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 尝试其他优化器\n",
    "params = torch.tensor([1.0,0.0],requires_grad=True)\n",
    "learning_rate=1e-1\n",
    "optimizer = optim.Adam([params],lr=learning_rate)\n",
    "training_loop(n_epochs=2000,optimizer=optimizer,params=params,t_u=t_u,t_c=t_c)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-13T06:02:48.497279400Z",
     "start_time": "2023-10-13T06:02:46.837264100Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "## 划分验证集和训练集"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "outputs": [
    {
     "data": {
      "text/plain": "(tensor([ 2,  6, 10,  7,  1,  0,  5,  8,  4]), tensor([3, 9]))"
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_samples=t_u.shape[0]\n",
    "n_val = int(0.2*n_samples)\n",
    "\n",
    "shuffled_indices = torch.randperm(n_samples)\n",
    "\n",
    "train_indices = shuffled_indices[:-n_val]\n",
    "val_indices = shuffled_indices[-n_val:]\n",
    "train_indices,val_indices"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-13T06:27:48.590810900Z",
     "start_time": "2023-10-13T06:27:48.204843Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "outputs": [],
   "source": [
    "train_t_u = t_u[train_indices]\n",
    "train_t_c = t_c[train_indices]\n",
    "\n",
    "val_t_u = t_u[val_indices]\n",
    "val_t_c = t_c[val_indices]\n",
    "\n",
    "train_t_un = 0.1*train_t_u\n",
    "val_t_un = 0.1*val_t_u"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-13T06:30:09.519946600Z",
     "start_time": "2023-10-13T06:30:09.380947800Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "outputs": [],
   "source": [
    "def training_loop(n_epochs,optimizer,params,train_t_u,val_t_u,train_t_c,val_t_c):\n",
    "    for epoch in range(1+n_epochs+1):\n",
    "        train_t_p = model(train_t_u,*params)\n",
    "        train_loss = loss_fn(train_t_p,train_t_c)\n",
    "\n",
    "        val_t_p = model(val_t_u,*params)\n",
    "        val_loss = loss_fn(val_t_p,val_t_c)\n",
    "\n",
    "        optimizer.zero_grad()\n",
    "        train_loss.backward()\n",
    "        optimizer.step()\n",
    "\n",
    "        if epoch <=3 or epoch%500==0:\n",
    "            print(f'Epoch{epoch},Training loss {train_loss.item():.4f},'\n",
    "                  f\"Validation loss {val_loss.item():.4f}\"\n",
    "                  )\n",
    "    return params"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-13T06:43:58.853614300Z",
     "start_time": "2023-10-13T06:43:58.838554300Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch0,Training loss 49.2367,Validation loss 220.4388\n",
      "Epoch1,Training loss 30.5863,Validation loss 130.6718\n",
      "Epoch2,Training loss 26.0094,Validation loss 96.0193\n",
      "Epoch3,Training loss 24.8496,Validation loss 81.2117\n",
      "Epoch500,Training loss 7.8263,Validation loss 20.9990\n",
      "Epoch1000,Training loss 3.9834,Validation loss 8.6973\n",
      "Epoch1500,Training loss 3.1077,Validation loss 5.2482\n",
      "Epoch2000,Training loss 2.9081,Validation loss 4.1539\n",
      "Epoch2500,Training loss 2.8627,Validation loss 3.7573\n",
      "Epoch3000,Training loss 2.8523,Validation loss 3.5967\n"
     ]
    },
    {
     "data": {
      "text/plain": "tensor([  5.2168, -16.4874], requires_grad=True)"
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "params = torch.tensor([1.0,0.0],requires_grad=True)\n",
    "learning_rate=1e-2\n",
    "optimizer = optim.SGD([params],lr=learning_rate)\n",
    "\n",
    "training_loop(\n",
    "    n_epochs=3000,\n",
    "    optimizer=optimizer,\n",
    "    params=params,\n",
    "    train_t_u=train_t_un,\n",
    "    val_t_u=val_t_un,\n",
    "    train_t_c=train_t_c,\n",
    "    val_t_c=val_t_c\n",
    ")"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-13T06:44:01.029551400Z",
     "start_time": "2023-10-13T06:43:59.743547200Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
